Overview

Dataset statistics

Number of variables367
Number of observations42962
Missing cells2217201
Missing cells (%)14.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory128.8 MiB
Average record size in memory3.1 KiB

Variable types

NUM328
CAT32
BOOL7

Warnings

EINGEFUEGT_AM has a high cardinality: 1599 distinct values High cardinality
AKT_DAT_KL has 6969 (16.2%) missing values Missing
ALTER_HH has 6969 (16.2%) missing values Missing
ALTER_KIND1 has 40974 (95.4%) missing values Missing
ALTER_KIND2 has 42206 (98.2%) missing values Missing
ALTER_KIND3 has 42788 (99.6%) missing values Missing
ALTER_KIND4 has 42921 (99.9%) missing values Missing
ALTERSKATEGORIE_FEIN has 8155 (19.0%) missing values Missing
ANZ_HAUSHALTE_AKTIV has 7777 (18.1%) missing values Missing
ANZ_HH_TITEL has 8246 (19.2%) missing values Missing
ANZ_KINDER has 6969 (16.2%) missing values Missing
ANZ_PERSONEN has 6969 (16.2%) missing values Missing
ANZ_STATISTISCHE_HAUSHALTE has 7777 (18.1%) missing values Missing
ANZ_TITEL has 6969 (16.2%) missing values Missing
ARBEIT has 7951 (18.5%) missing values Missing
BALLRAUM has 7799 (18.2%) missing values Missing
CAMEO_DEU_2015 has 7888 (18.4%) missing values Missing
CAMEO_DEUG_2015 has 7899 (18.4%) missing values Missing
CAMEO_INTL_2015 has 7899 (18.4%) missing values Missing
CJT_GESAMTTYP has 605 (1.4%) missing values Missing
CJT_KATALOGNUTZER has 605 (1.4%) missing values Missing
CJT_TYP_1 has 605 (1.4%) missing values Missing
CJT_TYP_2 has 605 (1.4%) missing values Missing
CJT_TYP_3 has 605 (1.4%) missing values Missing
CJT_TYP_4 has 605 (1.4%) missing values Missing
CJT_TYP_5 has 605 (1.4%) missing values Missing
CJT_TYP_6 has 605 (1.4%) missing values Missing
D19_BANKEN_ONLINE_QUOTE_12 has 7584 (17.7%) missing values Missing
D19_GESAMT_ONLINE_QUOTE_12 has 7584 (17.7%) missing values Missing
D19_KONSUMTYP has 7584 (17.7%) missing values Missing
D19_LETZTER_KAUF_BRANCHE has 7584 (17.7%) missing values Missing
D19_LOTTO has 7584 (17.7%) missing values Missing
D19_SOZIALES has 7584 (17.7%) missing values Missing
D19_TELKO_ONLINE_QUOTE_12 has 7584 (17.7%) missing values Missing
D19_VERSAND_ONLINE_QUOTE_12 has 7584 (17.7%) missing values Missing
D19_VERSI_ONLINE_QUOTE_12 has 7584 (17.7%) missing values Missing
DSL_FLAG has 7777 (18.1%) missing values Missing
EINGEFUEGT_AM has 7777 (18.1%) missing values Missing
EINGEZOGENAM_HH_JAHR has 6969 (16.2%) missing values Missing
EWDICHTE has 7799 (18.2%) missing values Missing
EXTSEL992 has 15948 (37.1%) missing values Missing
FIRMENDICHTE has 7777 (18.1%) missing values Missing
GEBAEUDETYP has 7777 (18.1%) missing values Missing
GEBAEUDETYP_RASTER has 7777 (18.1%) missing values Missing
GEMEINDETYP has 7955 (18.5%) missing values Missing
GFK_URLAUBERTYP has 605 (1.4%) missing values Missing
HH_DELTA_FLAG has 9678 (22.5%) missing values Missing
HH_EINKOMMEN_SCORE has 704 (1.6%) missing values Missing
INNENSTADT has 7799 (18.2%) missing values Missing
KBA05_ALTER1 has 8648 (20.1%) missing values Missing
KBA05_ALTER2 has 8648 (20.1%) missing values Missing
KBA05_ALTER3 has 8648 (20.1%) missing values Missing
KBA05_ALTER4 has 8648 (20.1%) missing values Missing
KBA05_ANHANG has 8648 (20.1%) missing values Missing
KBA05_ANTG1 has 8648 (20.1%) missing values Missing
KBA05_ANTG2 has 8648 (20.1%) missing values Missing
KBA05_ANTG3 has 8648 (20.1%) missing values Missing
KBA05_ANTG4 has 8648 (20.1%) missing values Missing
KBA05_AUTOQUOT has 8648 (20.1%) missing values Missing
KBA05_BAUMAX has 8648 (20.1%) missing values Missing
KBA05_CCM1 has 8648 (20.1%) missing values Missing
KBA05_CCM2 has 8648 (20.1%) missing values Missing
KBA05_CCM3 has 8648 (20.1%) missing values Missing
KBA05_CCM4 has 8648 (20.1%) missing values Missing
KBA05_DIESEL has 8648 (20.1%) missing values Missing
KBA05_FRAU has 8648 (20.1%) missing values Missing
KBA05_GBZ has 8648 (20.1%) missing values Missing
KBA05_HERST1 has 8648 (20.1%) missing values Missing
KBA05_HERST2 has 8648 (20.1%) missing values Missing
KBA05_HERST3 has 8648 (20.1%) missing values Missing
KBA05_HERST4 has 8648 (20.1%) missing values Missing
KBA05_HERST5 has 8648 (20.1%) missing values Missing
KBA05_HERSTTEMP has 7777 (18.1%) missing values Missing
KBA05_KRSAQUOT has 8648 (20.1%) missing values Missing
KBA05_KRSHERST1 has 8648 (20.1%) missing values Missing
KBA05_KRSHERST2 has 8648 (20.1%) missing values Missing
KBA05_KRSHERST3 has 8648 (20.1%) missing values Missing
KBA05_KRSKLEIN has 8648 (20.1%) missing values Missing
KBA05_KRSOBER has 8648 (20.1%) missing values Missing
KBA05_KRSVAN has 8648 (20.1%) missing values Missing
KBA05_KRSZUL has 8648 (20.1%) missing values Missing
KBA05_KW1 has 8648 (20.1%) missing values Missing
KBA05_KW2 has 8648 (20.1%) missing values Missing
KBA05_KW3 has 8648 (20.1%) missing values Missing
KBA05_MAXAH has 8648 (20.1%) missing values Missing
KBA05_MAXBJ has 8648 (20.1%) missing values Missing
KBA05_MAXHERST has 8648 (20.1%) missing values Missing
KBA05_MAXSEG has 8648 (20.1%) missing values Missing
KBA05_MAXVORB has 8648 (20.1%) missing values Missing
KBA05_MOD1 has 8648 (20.1%) missing values Missing
KBA05_MOD2 has 8648 (20.1%) missing values Missing
KBA05_MOD3 has 8648 (20.1%) missing values Missing
KBA05_MOD4 has 8648 (20.1%) missing values Missing
KBA05_MOD8 has 8648 (20.1%) missing values Missing
KBA05_MODTEMP has 7777 (18.1%) missing values Missing
KBA05_MOTOR has 8648 (20.1%) missing values Missing
KBA05_MOTRAD has 8648 (20.1%) missing values Missing
KBA05_SEG1 has 8648 (20.1%) missing values Missing
KBA05_SEG10 has 8648 (20.1%) missing values Missing
KBA05_SEG2 has 8648 (20.1%) missing values Missing
KBA05_SEG3 has 8648 (20.1%) missing values Missing
KBA05_SEG4 has 8648 (20.1%) missing values Missing
KBA05_SEG5 has 8648 (20.1%) missing values Missing
KBA05_SEG6 has 8648 (20.1%) missing values Missing
KBA05_SEG7 has 8648 (20.1%) missing values Missing
KBA05_SEG8 has 8648 (20.1%) missing values Missing
KBA05_SEG9 has 8648 (20.1%) missing values Missing
KBA05_VORB0 has 8648 (20.1%) missing values Missing
KBA05_VORB1 has 8648 (20.1%) missing values Missing
KBA05_VORB2 has 8648 (20.1%) missing values Missing
KBA05_ZUL1 has 8648 (20.1%) missing values Missing
KBA05_ZUL2 has 8648 (20.1%) missing values Missing
KBA05_ZUL3 has 8648 (20.1%) missing values Missing
KBA05_ZUL4 has 8648 (20.1%) missing values Missing
KBA13_ALTERHALTER_30 has 7962 (18.5%) missing values Missing
KBA13_ALTERHALTER_45 has 7962 (18.5%) missing values Missing
KBA13_ALTERHALTER_60 has 7962 (18.5%) missing values Missing
KBA13_ALTERHALTER_61 has 7962 (18.5%) missing values Missing
KBA13_ANTG1 has 7962 (18.5%) missing values Missing
KBA13_ANTG2 has 7962 (18.5%) missing values Missing
KBA13_ANTG3 has 7962 (18.5%) missing values Missing
KBA13_ANTG4 has 7962 (18.5%) missing values Missing
KBA13_ANZAHL_PKW has 7962 (18.5%) missing values Missing
KBA13_AUDI has 7962 (18.5%) missing values Missing
KBA13_AUTOQUOTE has 7962 (18.5%) missing values Missing
KBA13_BAUMAX has 7962 (18.5%) missing values Missing
KBA13_BJ_1999 has 7962 (18.5%) missing values Missing
KBA13_BJ_2000 has 7962 (18.5%) missing values Missing
KBA13_BJ_2004 has 7962 (18.5%) missing values Missing
KBA13_BJ_2006 has 7962 (18.5%) missing values Missing
KBA13_BJ_2008 has 7962 (18.5%) missing values Missing
KBA13_BJ_2009 has 7962 (18.5%) missing values Missing
KBA13_BMW has 7962 (18.5%) missing values Missing
KBA13_CCM_0_1400 has 7962 (18.5%) missing values Missing
KBA13_CCM_1000 has 7962 (18.5%) missing values Missing
KBA13_CCM_1200 has 7962 (18.5%) missing values Missing
KBA13_CCM_1400 has 7962 (18.5%) missing values Missing
KBA13_CCM_1401_2500 has 7962 (18.5%) missing values Missing
KBA13_CCM_1500 has 7962 (18.5%) missing values Missing
KBA13_CCM_1600 has 7962 (18.5%) missing values Missing
KBA13_CCM_1800 has 7962 (18.5%) missing values Missing
KBA13_CCM_2000 has 7962 (18.5%) missing values Missing
KBA13_CCM_2500 has 7962 (18.5%) missing values Missing
KBA13_CCM_2501 has 7962 (18.5%) missing values Missing
KBA13_CCM_3000 has 7962 (18.5%) missing values Missing
KBA13_CCM_3001 has 7962 (18.5%) missing values Missing
KBA13_FAB_ASIEN has 7962 (18.5%) missing values Missing
KBA13_FAB_SONSTIGE has 7962 (18.5%) missing values Missing
KBA13_FIAT has 7962 (18.5%) missing values Missing
KBA13_FORD has 7962 (18.5%) missing values Missing
KBA13_GBZ has 7962 (18.5%) missing values Missing
KBA13_HALTER_20 has 7962 (18.5%) missing values Missing
KBA13_HALTER_25 has 7962 (18.5%) missing values Missing
KBA13_HALTER_30 has 7962 (18.5%) missing values Missing
KBA13_HALTER_35 has 7962 (18.5%) missing values Missing
KBA13_HALTER_40 has 7962 (18.5%) missing values Missing
KBA13_HALTER_45 has 7962 (18.5%) missing values Missing
KBA13_HALTER_50 has 7962 (18.5%) missing values Missing
KBA13_HALTER_55 has 7962 (18.5%) missing values Missing
KBA13_HALTER_60 has 7962 (18.5%) missing values Missing
KBA13_HALTER_65 has 7962 (18.5%) missing values Missing
KBA13_HALTER_66 has 7962 (18.5%) missing values Missing
KBA13_HERST_ASIEN has 7962 (18.5%) missing values Missing
KBA13_HERST_AUDI_VW has 7962 (18.5%) missing values Missing
KBA13_HERST_BMW_BENZ has 7962 (18.5%) missing values Missing
KBA13_HERST_EUROPA has 7962 (18.5%) missing values Missing
KBA13_HERST_FORD_OPEL has 7962 (18.5%) missing values Missing
KBA13_HERST_SONST has 7962 (18.5%) missing values Missing
KBA13_HHZ has 7962 (18.5%) missing values Missing
KBA13_KMH_0_140 has 7962 (18.5%) missing values Missing
KBA13_KMH_110 has 7962 (18.5%) missing values Missing
KBA13_KMH_140 has 7962 (18.5%) missing values Missing
KBA13_KMH_140_210 has 7962 (18.5%) missing values Missing
KBA13_KMH_180 has 7962 (18.5%) missing values Missing
KBA13_KMH_210 has 7962 (18.5%) missing values Missing
KBA13_KMH_211 has 7962 (18.5%) missing values Missing
KBA13_KMH_250 has 7962 (18.5%) missing values Missing
KBA13_KMH_251 has 7962 (18.5%) missing values Missing
KBA13_KRSAQUOT has 7962 (18.5%) missing values Missing
KBA13_KRSHERST_AUDI_VW has 7962 (18.5%) missing values Missing
KBA13_KRSHERST_BMW_BENZ has 7962 (18.5%) missing values Missing
KBA13_KRSHERST_FORD_OPEL has 7962 (18.5%) missing values Missing
KBA13_KRSSEG_KLEIN has 7962 (18.5%) missing values Missing
KBA13_KRSSEG_OBER has 7962 (18.5%) missing values Missing
KBA13_KRSSEG_VAN has 7962 (18.5%) missing values Missing
KBA13_KRSZUL_NEU has 7962 (18.5%) missing values Missing
KBA13_KW_0_60 has 7962 (18.5%) missing values Missing
KBA13_KW_110 has 7962 (18.5%) missing values Missing
KBA13_KW_120 has 7962 (18.5%) missing values Missing
KBA13_KW_121 has 7962 (18.5%) missing values Missing
KBA13_KW_30 has 7962 (18.5%) missing values Missing
KBA13_KW_40 has 7962 (18.5%) missing values Missing
KBA13_KW_50 has 7962 (18.5%) missing values Missing
KBA13_KW_60 has 7962 (18.5%) missing values Missing
KBA13_KW_61_120 has 7962 (18.5%) missing values Missing
KBA13_KW_70 has 7962 (18.5%) missing values Missing
KBA13_KW_80 has 7962 (18.5%) missing values Missing
KBA13_KW_90 has 7962 (18.5%) missing values Missing
KBA13_MAZDA has 7962 (18.5%) missing values Missing
KBA13_MERCEDES has 7962 (18.5%) missing values Missing
KBA13_MOTOR has 7962 (18.5%) missing values Missing
KBA13_NISSAN has 7962 (18.5%) missing values Missing
KBA13_OPEL has 7962 (18.5%) missing values Missing
KBA13_PEUGEOT has 7962 (18.5%) missing values Missing
KBA13_RENAULT has 7962 (18.5%) missing values Missing
KBA13_SEG_GELAENDEWAGEN has 7962 (18.5%) missing values Missing
KBA13_SEG_GROSSRAUMVANS has 7962 (18.5%) missing values Missing
KBA13_SEG_KLEINST has 7962 (18.5%) missing values Missing
KBA13_SEG_KLEINWAGEN has 7962 (18.5%) missing values Missing
KBA13_SEG_KOMPAKTKLASSE has 7962 (18.5%) missing values Missing
KBA13_SEG_MINIVANS has 7962 (18.5%) missing values Missing
KBA13_SEG_MINIWAGEN has 7962 (18.5%) missing values Missing
KBA13_SEG_MITTELKLASSE has 7962 (18.5%) missing values Missing
KBA13_SEG_OBEREMITTELKLASSE has 7962 (18.5%) missing values Missing
KBA13_SEG_OBERKLASSE has 7962 (18.5%) missing values Missing
KBA13_SEG_SONSTIGE has 7962 (18.5%) missing values Missing
KBA13_SEG_SPORTWAGEN has 7962 (18.5%) missing values Missing
KBA13_SEG_UTILITIES has 7962 (18.5%) missing values Missing
KBA13_SEG_VAN has 7962 (18.5%) missing values Missing
KBA13_SEG_WOHNMOBILE has 7962 (18.5%) missing values Missing
KBA13_SITZE_4 has 7962 (18.5%) missing values Missing
KBA13_SITZE_5 has 7962 (18.5%) missing values Missing
KBA13_SITZE_6 has 7962 (18.5%) missing values Missing
KBA13_TOYOTA has 7962 (18.5%) missing values Missing
KBA13_VORB_0 has 7962 (18.5%) missing values Missing
KBA13_VORB_1 has 7962 (18.5%) missing values Missing
KBA13_VORB_1_2 has 7962 (18.5%) missing values Missing
KBA13_VORB_2 has 7962 (18.5%) missing values Missing
KBA13_VORB_3 has 7962 (18.5%) missing values Missing
KBA13_VW has 7962 (18.5%) missing values Missing
KK_KUNDENTYP has 25316 (58.9%) missing values Missing
KKK has 8445 (19.7%) missing values Missing
KONSUMNAEHE has 6997 (16.3%) missing values Missing
KONSUMZELLE has 7777 (18.1%) missing values Missing
LP_FAMILIE_FEIN has 605 (1.4%) missing values Missing
LP_FAMILIE_GROB has 605 (1.4%) missing values Missing
LP_LEBENSPHASE_FEIN has 605 (1.4%) missing values Missing
LP_LEBENSPHASE_GROB has 605 (1.4%) missing values Missing
LP_STATUS_FEIN has 605 (1.4%) missing values Missing
LP_STATUS_GROB has 605 (1.4%) missing values Missing
MIN_GEBAEUDEJAHR has 7777 (18.1%) missing values Missing
MOBI_RASTER has 7777 (18.1%) missing values Missing
MOBI_REGIO has 8648 (20.1%) missing values Missing
ONLINE_AFFINITAET has 605 (1.4%) missing values Missing
ORTSGR_KLS9 has 7951 (18.5%) missing values Missing
OST_WEST_KZ has 7777 (18.1%) missing values Missing
PLZ8_ANTG1 has 8153 (19.0%) missing values Missing
PLZ8_ANTG2 has 8153 (19.0%) missing values Missing
PLZ8_ANTG3 has 8153 (19.0%) missing values Missing
PLZ8_ANTG4 has 8153 (19.0%) missing values Missing
PLZ8_BAUMAX has 8153 (19.0%) missing values Missing
PLZ8_GBZ has 8153 (19.0%) missing values Missing
PLZ8_HHZ has 8153 (19.0%) missing values Missing
REGIOTYP has 8445 (19.7%) missing values Missing
RELAT_AB has 7951 (18.5%) missing values Missing
RETOURTYP_BK_S has 605 (1.4%) missing values Missing
RT_KEIN_ANREIZ has 605 (1.4%) missing values Missing
RT_SCHNAEPPCHEN has 605 (1.4%) missing values Missing
RT_UEBERGROESSE has 6380 (14.9%) missing values Missing
SOHO_KZ has 6969 (16.2%) missing values Missing
STRUKTURTYP has 7955 (18.5%) missing values Missing
TITEL_KZ has 6969 (16.2%) missing values Missing
UMFELD_ALT has 7925 (18.4%) missing values Missing
UMFELD_JUNG has 7925 (18.4%) missing values Missing
UNGLEICHENN_FLAG has 6969 (16.2%) missing values Missing
VERDICHTUNGSRAUM has 7955 (18.5%) missing values Missing
VHA has 6969 (16.2%) missing values Missing
VHN has 8445 (19.7%) missing values Missing
VK_DHT4A has 7267 (16.9%) missing values Missing
VK_DISTANZ has 7267 (16.9%) missing values Missing
VK_ZG11 has 7267 (16.9%) missing values Missing
W_KEIT_KIND_HH has 9678 (22.5%) missing values Missing
WOHNDAUER_2008 has 6969 (16.2%) missing values Missing
WOHNLAGE has 7777 (18.1%) missing values Missing
ANZ_HH_TITEL is highly skewed (γ1 = 21.40627383) Skewed
D19_VERSI_ONLINE_DATUM is highly skewed (γ1 = -20.21632487) Skewed
TITEL_KZ is highly skewed (γ1 = 25.64853276) Skewed
LNR has unique values Unique
AGER_TYP has 927 (2.2%) zeros Zeros
ALTER_HH has 6208 (14.4%) zeros Zeros
ALTERSKATEGORIE_FEIN has 3536 (8.2%) zeros Zeros
ANZ_HAUSHALTE_AKTIV has 530 (1.2%) zeros Zeros
ANZ_HH_TITEL has 33486 (77.9%) zeros Zeros
ANZ_KINDER has 33821 (78.7%) zeros Zeros
ANZ_PERSONEN has 2709 (6.3%) zeros Zeros
D19_BANKEN_ANZ_12 has 40198 (93.6%) zeros Zeros
D19_BANKEN_ANZ_24 has 38714 (90.1%) zeros Zeros
D19_BANKEN_DIREKT has 36805 (85.7%) zeros Zeros
D19_BANKEN_GROSS has 38760 (90.2%) zeros Zeros
D19_BANKEN_LOKAL has 42170 (98.2%) zeros Zeros
D19_BANKEN_ONLINE_QUOTE_12 has 33787 (78.6%) zeros Zeros
D19_BANKEN_REST has 39983 (93.1%) zeros Zeros
D19_BEKLEIDUNG_GEH has 35949 (83.7%) zeros Zeros
D19_BEKLEIDUNG_REST has 29981 (69.8%) zeros Zeros
D19_BILDUNG has 34895 (81.2%) zeros Zeros
D19_BIO_OEKO has 38422 (89.4%) zeros Zeros
D19_BUCH_CD has 22410 (52.2%) zeros Zeros
D19_DIGIT_SERV has 41226 (96.0%) zeros Zeros
D19_DROGERIEARTIKEL has 36725 (85.5%) zeros Zeros
D19_ENERGIE has 39064 (90.9%) zeros Zeros
D19_FREIZEIT has 37678 (87.7%) zeros Zeros
D19_GARTEN has 39737 (92.5%) zeros Zeros
D19_GESAMT_ANZ_12 has 25341 (59.0%) zeros Zeros
D19_GESAMT_ANZ_24 has 20736 (48.3%) zeros Zeros
D19_GESAMT_ONLINE_QUOTE_12 has 23291 (54.2%) zeros Zeros
D19_HANDWERK has 31086 (72.4%) zeros Zeros
D19_HAUS_DEKO has 28556 (66.5%) zeros Zeros
D19_KINDERARTIKEL has 33786 (78.6%) zeros Zeros
D19_KOSMETIK has 28919 (67.3%) zeros Zeros
D19_LEBENSMITTEL has 37467 (87.2%) zeros Zeros
D19_LOTTO has 20293 (47.2%) zeros Zeros
D19_NAHRUNGSERGAENZUNG has 38508 (89.6%) zeros Zeros
D19_RATGEBER has 35306 (82.2%) zeros Zeros
D19_REISEN has 28298 (65.9%) zeros Zeros
D19_SAMMELARTIKEL has 31986 (74.5%) zeros Zeros
D19_SCHUHE has 37508 (87.3%) zeros Zeros
D19_SONSTIGE has 15258 (35.5%) zeros Zeros
D19_SOZIALES has 9615 (22.4%) zeros Zeros
D19_TECHNIK has 25369 (59.0%) zeros Zeros
D19_TELKO_ANZ_12 has 41099 (95.7%) zeros Zeros
D19_TELKO_ANZ_24 has 39720 (92.5%) zeros Zeros
D19_TELKO_MOBILE has 36119 (84.1%) zeros Zeros
D19_TELKO_REST has 37986 (88.4%) zeros Zeros
D19_TIERARTIKEL has 40917 (95.2%) zeros Zeros
D19_VERSAND_ANZ_12 has 27763 (64.6%) zeros Zeros
D19_VERSAND_ANZ_24 has 23413 (54.5%) zeros Zeros
D19_VERSAND_ONLINE_QUOTE_12 has 24597 (57.3%) zeros Zeros
D19_VERSAND_REST has 36458 (84.9%) zeros Zeros
D19_VERSI_ANZ_12 has 39485 (91.9%) zeros Zeros
D19_VERSI_ANZ_24 has 37473 (87.2%) zeros Zeros
D19_VERSICHERUNGEN has 32015 (74.5%) zeros Zeros
D19_VOLLSORTIMENT has 20628 (48.0%) zeros Zeros
D19_WEIN_FEINKOST has 36950 (86.0%) zeros Zeros
GEBURTSJAHR has 17475 (40.7%) zeros Zeros
KBA05_ALTER1 has 5246 (12.2%) zeros Zeros
KBA05_ALTER4 has 830 (1.9%) zeros Zeros
KBA05_ANHANG has 9912 (23.1%) zeros Zeros
KBA05_ANTG1 has 9114 (21.2%) zeros Zeros
KBA05_ANTG2 has 12918 (30.1%) zeros Zeros
KBA05_BAUMAX has 14332 (33.4%) zeros Zeros
KBA05_CCM4 has 10887 (25.3%) zeros Zeros
KBA05_DIESEL has 2354 (5.5%) zeros Zeros
KBA05_HERST1 has 2645 (6.2%) zeros Zeros
KBA05_HERST3 has 600 (1.4%) zeros Zeros
KBA05_HERST4 has 1037 (2.4%) zeros Zeros
KBA05_HERST5 has 1641 (3.8%) zeros Zeros
KBA05_KW3 has 7676 (17.9%) zeros Zeros
KBA05_MOD1 has 11398 (26.5%) zeros Zeros
KBA05_MOD4 has 1672 (3.9%) zeros Zeros
KBA05_MOD8 has 8542 (19.9%) zeros Zeros
KBA05_MOTRAD has 8023 (18.7%) zeros Zeros
KBA05_SEG1 has 10321 (24.0%) zeros Zeros
KBA05_SEG10 has 3972 (9.2%) zeros Zeros
KBA05_SEG5 has 7092 (16.5%) zeros Zeros
KBA05_SEG7 has 15246 (35.5%) zeros Zeros
KBA05_SEG8 has 17259 (40.2%) zeros Zeros
KBA05_SEG9 has 10318 (24.0%) zeros Zeros
KBA05_VORB2 has 2781 (6.5%) zeros Zeros
KBA05_ZUL3 has 2023 (4.7%) zeros Zeros
KBA05_ZUL4 has 3181 (7.4%) zeros Zeros
KBA13_ANTG2 has 489 (1.1%) zeros Zeros
KBA13_BJ_2008 has 5588 (13.0%) zeros Zeros
KBA13_BJ_2009 has 4183 (9.7%) zeros Zeros
KBA13_CCM_0_1400 has 6654 (15.5%) zeros Zeros
KBA13_CCM_1000 has 4518 (10.5%) zeros Zeros
KBA13_CCM_1200 has 6800 (15.8%) zeros Zeros
KBA13_CCM_1800 has 5981 (13.9%) zeros Zeros
KBA13_CCM_2500 has 4153 (9.7%) zeros Zeros
KBA13_CCM_2501 has 3906 (9.1%) zeros Zeros
KBA13_CCM_3000 has 2500 (5.8%) zeros Zeros
KBA13_KMH_0_140 has 4632 (10.8%) zeros Zeros
KBA13_KMH_211 has 5978 (13.9%) zeros Zeros
KBA13_KMH_250 has 5985 (13.9%) zeros Zeros
KBA13_KW_110 has 5425 (12.6%) zeros Zeros
KBA13_KW_120 has 3940 (9.2%) zeros Zeros
KBA13_KW_121 has 4018 (9.4%) zeros Zeros
KBA13_KW_40 has 4534 (10.6%) zeros Zeros
KBA13_KW_50 has 6649 (15.5%) zeros Zeros
KBA13_KW_60 has 6069 (14.1%) zeros Zeros
KBA13_KW_70 has 6422 (14.9%) zeros Zeros
KBA13_KW_80 has 5746 (13.4%) zeros Zeros
KBA13_KW_90 has 5936 (13.8%) zeros Zeros
KBA13_SEG_OBERKLASSE has 3823 (8.9%) zeros Zeros
KBA13_SEG_SPORTWAGEN has 3526 (8.2%) zeros Zeros
KBA13_SEG_WOHNMOBILE has 3870 (9.0%) zeros Zeros
KBA13_VORB_3 has 7228 (16.8%) zeros Zeros
KKK has 1485 (3.5%) zeros Zeros
LP_FAMILIE_FEIN has 8208 (19.1%) zeros Zeros
LP_FAMILIE_GROB has 8208 (19.1%) zeros Zeros
LP_LEBENSPHASE_FEIN has 8298 (19.3%) zeros Zeros
LP_LEBENSPHASE_GROB has 8273 (19.3%) zeros Zeros
ONLINE_AFFINITAET has 2156 (5.0%) zeros Zeros
PRAEGENDE_JUGENDJAHRE has 7454 (17.4%) zeros Zeros
REGIOTYP has 1485 (3.5%) zeros Zeros
SHOPPER_TYP has 6034 (14.0%) zeros Zeros
TITEL_KZ has 35780 (83.3%) zeros Zeros
VERDICHTUNGSRAUM has 17087 (39.8%) zeros Zeros
VHA has 16176 (37.7%) zeros Zeros
VHN has 1485 (3.5%) zeros Zeros
W_KEIT_KIND_HH has 739 (1.7%) zeros Zeros

Reproduction

Analysis started2020-11-30 14:56:22.901648
Analysis finished2020-11-30 14:56:29.173052
Duration6.27 seconds
Software versionpandas-profiling v2.9.0
Download configurationconfig.yaml

Variables

LNR
Real number (ℝ≥0)

UNIQUE

Distinct42962
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean42803.12013
Minimum1
Maximum85795
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:56:29.281229image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4203.05
Q121284.25
median42710
Q364340.5
95-th percentile81345.9
Maximum85795
Range85794
Interquartile range (IQR)43056.25

Descriptive statistics

Standard deviation24778.33998
Coefficient of variation (CV)0.5788909759
Kurtosis-1.203373177
Mean42803.12013
Median Absolute Deviation (MAD)21506
Skewness0.002154314123
Sum1838907647
Variance613966132.4
MonotocityNot monotonic
2020-11-30T23:56:29.399672image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
20471< 0.1%
 
811971< 0.1%
 
689071< 0.1%
 
730011< 0.1%
 
709521< 0.1%
 
279431< 0.1%
 
320371< 0.1%
 
217921< 0.1%
 
443191< 0.1%
 
422701< 0.1%
 
71081< 0.1%
 
402171< 0.1%
 
381681< 0.1%
 
586461< 0.1%
 
647891< 0.1%
 
658471< 0.1%
 
165861< 0.1%
 
115351< 0.1%
 
811651< 0.1%
 
136121< 0.1%
 
95181< 0.1%
 
668261< 0.1%
 
545761< 0.1%
 
136441< 0.1%
 
34031< 0.1%
 
Other values (42937)4293799.9%
 
ValueCountFrequency (%) 
11< 0.1%
 
51< 0.1%
 
91< 0.1%
 
101< 0.1%
 
111< 0.1%
 
121< 0.1%
 
131< 0.1%
 
141< 0.1%
 
191< 0.1%
 
211< 0.1%
 
ValueCountFrequency (%) 
857951< 0.1%
 
857921< 0.1%
 
857881< 0.1%
 
857861< 0.1%
 
857821< 0.1%
 
857761< 0.1%
 
857751< 0.1%
 
857741< 0.1%
 
857731< 0.1%
 
857711< 0.1%
 

AGER_TYP
Real number (ℝ)

ZEROS

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.5429216517
Minimum-1
Maximum3
Zeros927
Zeros (%)2.2%
Memory size335.8 KiB
2020-11-30T23:56:29.498368image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum-1
5-th percentile-1
Q1-1
median1
Q32
95-th percentile3
Maximum3
Range4
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.412923822
Coefficient of variation (CV)2.602445155
Kurtosis-1.569175881
Mean0.5429216517
Median Absolute Deviation (MAD)1
Skewness0.07039473986
Sum23325
Variance1.996353727
MonotocityNot monotonic
2020-11-30T23:56:29.584266image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
-11796341.8%
 
21247029.0%
 
1922921.5%
 
323735.5%
 
09272.2%
 
ValueCountFrequency (%) 
-11796341.8%
 
09272.2%
 
1922921.5%
 
21247029.0%
 
323735.5%
 
ValueCountFrequency (%) 
323735.5%
 
21247029.0%
 
1922921.5%
 
09272.2%
 
-11796341.8%
 

AKT_DAT_KL
Real number (ℝ≥0)

MISSING

Distinct9
Distinct (%)< 0.1%
Missing6969
Missing (%)16.2%
Infinite0
Infinite (%)0.0%
Mean1.525241019
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:56:29.676178image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile6
Maximum9
Range8
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.741499841
Coefficient of variation (CV)1.141786655
Kurtosis10.97107406
Mean1.525241019
Median Absolute Deviation (MAD)0
Skewness3.476977401
Sum54898
Variance3.032821697
MonotocityNot monotonic
2020-11-30T23:56:29.758823image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%) 
13199974.5%
 
911952.8%
 
27881.8%
 
55021.2%
 
34030.9%
 
62980.7%
 
42810.7%
 
72790.6%
 
82480.6%
 
(Missing)696916.2%
 
ValueCountFrequency (%) 
13199974.5%
 
27881.8%
 
34030.9%
 
42810.7%
 
55021.2%
 
62980.7%
 
72790.6%
 
82480.6%
 
911952.8%
 
ValueCountFrequency (%) 
911952.8%
 
82480.6%
 
72790.6%
 
62980.7%
 
55021.2%
 
42810.7%
 
34030.9%
 
27881.8%
 
13199974.5%
 

ALTER_HH
Real number (ℝ≥0)

MISSING
ZEROS

Distinct20
Distinct (%)0.1%
Missing6969
Missing (%)16.2%
Infinite0
Infinite (%)0.0%
Mean10.28555552
Minimum0
Maximum21
Zeros6208
Zeros (%)14.4%
Memory size335.8 KiB
2020-11-30T23:56:29.857013image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q18
median10
Q315
95-th percentile20
Maximum21
Range21
Interquartile range (IQR)7

Descriptive statistics

Standard deviation6.08260965
Coefficient of variation (CV)0.591373955
Kurtosis-0.6426953343
Mean10.28555552
Median Absolute Deviation (MAD)3
Skewness-0.2225836314
Sum370208
Variance36.99814015
MonotocityNot monotonic
2020-11-30T23:56:29.947102image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%) 
0620814.4%
 
939229.1%
 
1037758.8%
 
827016.3%
 
1122765.3%
 
1221355.0%
 
717494.1%
 
1316443.8%
 
1515593.6%
 
1415083.5%
 
2114123.3%
 
1613563.2%
 
1912552.9%
 
1712452.9%
 
2012162.8%
 
1811752.7%
 
67051.6%
 
51220.3%
 
4260.1%
 
34< 0.1%
 
(Missing)696916.2%
 
ValueCountFrequency (%) 
0620814.4%
 
34< 0.1%
 
4260.1%
 
51220.3%
 
67051.6%
 
717494.1%
 
827016.3%
 
939229.1%
 
1037758.8%
 
1122765.3%
 
ValueCountFrequency (%) 
2114123.3%
 
2012162.8%
 
1912552.9%
 
1811752.7%
 
1712452.9%
 
1613563.2%
 
1515593.6%
 
1415083.5%
 
1316443.8%
 
1221355.0%
 

ALTER_KIND1
Real number (ℝ≥0)

MISSING

Distinct17
Distinct (%)0.9%
Missing40974
Missing (%)95.4%
Infinite0
Infinite (%)0.0%
Mean12.60613682
Minimum2
Maximum18
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:56:30.034826image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile6
Q19
median13
Q316
95-th percentile18
Maximum18
Range16
Interquartile range (IQR)7

Descriptive statistics

Standard deviation3.924976167
Coefficient of variation (CV)0.3113544001
Kurtosis-0.9142784002
Mean12.60613682
Median Absolute Deviation (MAD)3
Skewness-0.3489802568
Sum25061
Variance15.40543791
MonotocityNot monotonic
2020-11-30T23:56:30.120997image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%) 
182230.5%
 
171970.5%
 
151860.4%
 
141650.4%
 
161600.4%
 
131540.4%
 
101380.3%
 
121330.3%
 
111290.3%
 
91270.3%
 
81250.3%
 
71080.3%
 
6830.2%
 
5240.1%
 
420< 0.1%
 
312< 0.1%
 
24< 0.1%
 
(Missing)4097495.4%
 
ValueCountFrequency (%) 
24< 0.1%
 
312< 0.1%
 
420< 0.1%
 
5240.1%
 
6830.2%
 
71080.3%
 
81250.3%
 
91270.3%
 
101380.3%
 
111290.3%
 
ValueCountFrequency (%) 
182230.5%
 
171970.5%
 
161600.4%
 
151860.4%
 
141650.4%
 
131540.4%
 
121330.3%
 
111290.3%
 
101380.3%
 
91270.3%
 

ALTER_KIND2
Real number (ℝ≥0)

MISSING

Distinct14
Distinct (%)1.9%
Missing42206
Missing (%)98.2%
Infinite0
Infinite (%)0.0%
Mean13.78306878
Minimum5
Maximum18
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:56:30.211651image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile8
Q112
median14
Q316
95-th percentile18
Maximum18
Range13
Interquartile range (IQR)4

Descriptive statistics

Standard deviation3.065817368
Coefficient of variation (CV)0.2224335825
Kurtosis-0.5390706746
Mean13.78306878
Median Absolute Deviation (MAD)2
Skewness-0.461868109
Sum10420
Variance9.399236133
MonotocityNot monotonic
2020-11-30T23:56:30.305445image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%) 
17990.2%
 
12870.2%
 
18870.2%
 
14800.2%
 
15790.2%
 
16770.2%
 
13720.2%
 
11580.1%
 
10420.1%
 
9310.1%
 
8220.1%
 
713< 0.1%
 
65< 0.1%
 
54< 0.1%
 
(Missing)4220698.2%
 
ValueCountFrequency (%) 
54< 0.1%
 
65< 0.1%
 
713< 0.1%
 
8220.1%
 
9310.1%
 
10420.1%
 
11580.1%
 
12870.2%
 
13720.2%
 
14800.2%
 
ValueCountFrequency (%) 
18870.2%
 
17990.2%
 
16770.2%
 
15790.2%
 
14800.2%
 
13720.2%
 
12870.2%
 
11580.1%
 
10420.1%
 
9310.1%
 

ALTER_KIND3
Real number (ℝ≥0)

MISSING

Distinct12
Distinct (%)6.9%
Missing42788
Missing (%)99.6%
Infinite0
Infinite (%)0.0%
Mean14.65517241
Minimum6
Maximum18
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:56:30.387804image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum6
5-th percentile10
Q113
median15
Q317
95-th percentile18
Maximum18
Range12
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.615328696
Coefficient of variation (CV)0.1784577228
Kurtosis0.5828992821
Mean14.65517241
Median Absolute Deviation (MAD)2
Skewness-0.7684269368
Sum2550
Variance6.83994419
MonotocityNot monotonic
2020-11-30T23:56:30.476679image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%) 
18280.1%
 
14270.1%
 
17240.1%
 
13230.1%
 
15220.1%
 
1619< 0.1%
 
1214< 0.1%
 
116< 0.1%
 
105< 0.1%
 
73< 0.1%
 
82< 0.1%
 
61< 0.1%
 
(Missing)4278899.6%
 
ValueCountFrequency (%) 
61< 0.1%
 
73< 0.1%
 
82< 0.1%
 
105< 0.1%
 
116< 0.1%
 
1214< 0.1%
 
13230.1%
 
14270.1%
 
15220.1%
 
1619< 0.1%
 
ValueCountFrequency (%) 
18280.1%
 
17240.1%
 
1619< 0.1%
 
15220.1%
 
14270.1%
 
13230.1%
 
1214< 0.1%
 
116< 0.1%
 
105< 0.1%
 
82< 0.1%
 

ALTER_KIND4
Real number (ℝ≥0)

MISSING

Distinct11
Distinct (%)26.8%
Missing42921
Missing (%)99.9%
Infinite0
Infinite (%)0.0%
Mean14.19512195
Minimum6
Maximum18
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:56:30.558785image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum6
5-th percentile7
Q113
median15
Q317
95-th percentile18
Maximum18
Range12
Interquartile range (IQR)4

Descriptive statistics

Standard deviation3.034958914
Coefficient of variation (CV)0.2138029476
Kurtosis0.8474975887
Mean14.19512195
Median Absolute Deviation (MAD)2
Skewness-0.9796221834
Sum582
Variance9.21097561
MonotocityNot monotonic
2020-11-30T23:56:30.648527image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%) 
156< 0.1%
 
136< 0.1%
 
176< 0.1%
 
145< 0.1%
 
185< 0.1%
 
164< 0.1%
 
123< 0.1%
 
72< 0.1%
 
112< 0.1%
 
61< 0.1%
 
101< 0.1%
 
(Missing)4292199.9%
 
ValueCountFrequency (%) 
61< 0.1%
 
72< 0.1%
 
101< 0.1%
 
112< 0.1%
 
123< 0.1%
 
136< 0.1%
 
145< 0.1%
 
156< 0.1%
 
164< 0.1%
 
176< 0.1%
 
ValueCountFrequency (%) 
185< 0.1%
 
176< 0.1%
 
164< 0.1%
 
156< 0.1%
 
145< 0.1%
 
136< 0.1%
 
123< 0.1%
 
112< 0.1%
 
101< 0.1%
 
72< 0.1%
 

ALTERSKATEGORIE_FEIN
Real number (ℝ≥0)

MISSING
ZEROS

Distinct25
Distinct (%)0.1%
Missing8155
Missing (%)19.0%
Infinite0
Infinite (%)0.0%
Mean9.855057891
Minimum0
Maximum25
Zeros3536
Zeros (%)8.2%
Memory size335.8 KiB
2020-11-30T23:56:30.743812image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q18
median10
Q313
95-th percentile16
Maximum25
Range25
Interquartile range (IQR)5

Descriptive statistics

Standard deviation4.373539165
Coefficient of variation (CV)0.443786248
Kurtosis0.705776336
Mean9.855057891
Median Absolute Deviation (MAD)2
Skewness-0.6138376707
Sum343025
Variance19.12784483
MonotocityNot monotonic
2020-11-30T23:56:30.863292image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%) 
9504511.7%
 
10468110.9%
 
035368.2%
 
833327.8%
 
1231887.4%
 
1130497.1%
 
1326536.2%
 
1422315.2%
 
720664.8%
 
1516053.7%
 
169032.1%
 
68191.9%
 
175571.3%
 
184050.9%
 
192760.6%
 
201750.4%
 
51360.3%
 
21610.1%
 
4330.1%
 
2421< 0.1%
 
2518< 0.1%
 
39< 0.1%
 
234< 0.1%
 
223< 0.1%
 
21< 0.1%
 
(Missing)815519.0%
 
ValueCountFrequency (%) 
035368.2%
 
21< 0.1%
 
39< 0.1%
 
4330.1%
 
51360.3%
 
68191.9%
 
720664.8%
 
833327.8%
 
9504511.7%
 
10468110.9%
 
ValueCountFrequency (%) 
2518< 0.1%
 
2421< 0.1%
 
234< 0.1%
 
223< 0.1%
 
21610.1%
 
201750.4%
 
192760.6%
 
184050.9%
 
175571.3%
 
169032.1%
 

ANZ_HAUSHALTE_AKTIV
Real number (ℝ≥0)

MISSING
ZEROS

Distinct175
Distinct (%)0.5%
Missing7777
Missing (%)18.1%
Infinite0
Infinite (%)0.0%
Mean6.706096348
Minimum0
Maximum438
Zeros530
Zeros (%)1.2%
Memory size335.8 KiB
2020-11-30T23:56:30.994715image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median2
Q37
95-th percentile26
Maximum438
Range438
Interquartile range (IQR)6

Descriptive statistics

Standard deviation15.15178973
Coefficient of variation (CV)2.259405315
Kurtosis137.5348484
Mean6.706096348
Median Absolute Deviation (MAD)1
Skewness9.140196724
Sum235954
Variance229.5767321
MonotocityNot monotonic
2020-11-30T23:56:31.115392image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
11381632.2%
 
2543712.7%
 
321885.1%
 
413583.2%
 
611932.8%
 
511902.8%
 
711552.7%
 
810702.5%
 
99442.2%
 
108211.9%
 
116191.4%
 
05301.2%
 
125091.2%
 
134321.0%
 
143400.8%
 
153160.7%
 
162540.6%
 
172110.5%
 
181830.4%
 
201650.4%
 
191590.4%
 
211340.3%
 
221010.2%
 
23990.2%
 
29960.2%
 
Other values (150)18654.3%
 
(Missing)777718.1%
 
ValueCountFrequency (%) 
05301.2%
 
11381632.2%
 
2543712.7%
 
321885.1%
 
413583.2%
 
511902.8%
 
611932.8%
 
711552.7%
 
810702.5%
 
99442.2%
 
ValueCountFrequency (%) 
4381< 0.1%
 
3531< 0.1%
 
3472< 0.1%
 
3441< 0.1%
 
3331< 0.1%
 
3211< 0.1%
 
3111< 0.1%
 
3052< 0.1%
 
3041< 0.1%
 
2903< 0.1%
 

ANZ_HH_TITEL
Real number (ℝ≥0)

MISSING
SKEWED
ZEROS

Distinct15
Distinct (%)< 0.1%
Missing8246
Missing (%)19.2%
Infinite0
Infinite (%)0.0%
Mean0.0495736836
Minimum0
Maximum20
Zeros33486
Zeros (%)77.9%
Memory size335.8 KiB
2020-11-30T23:56:31.242912image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum20
Range20
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.3803348241
Coefficient of variation (CV)7.67211142
Kurtosis739.8139452
Mean0.0495736836
Median Absolute Deviation (MAD)0
Skewness21.40627383
Sum1721
Variance0.1446545784
MonotocityNot monotonic
2020-11-30T23:56:31.363526image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%) 
03348677.9%
 
110382.4%
 
21010.2%
 
3390.1%
 
417< 0.1%
 
59< 0.1%
 
66< 0.1%
 
74< 0.1%
 
94< 0.1%
 
84< 0.1%
 
133< 0.1%
 
172< 0.1%
 
201< 0.1%
 
141< 0.1%
 
121< 0.1%
 
(Missing)824619.2%
 
ValueCountFrequency (%) 
03348677.9%
 
110382.4%
 
21010.2%
 
3390.1%
 
417< 0.1%
 
59< 0.1%
 
66< 0.1%
 
74< 0.1%
 
84< 0.1%
 
94< 0.1%
 
ValueCountFrequency (%) 
201< 0.1%
 
172< 0.1%
 
141< 0.1%
 
133< 0.1%
 
121< 0.1%
 
94< 0.1%
 
84< 0.1%
 
74< 0.1%
 
66< 0.1%
 
59< 0.1%
 

ANZ_KINDER
Real number (ℝ≥0)

MISSING
ZEROS

Distinct7
Distinct (%)< 0.1%
Missing6969
Missing (%)16.2%
Infinite0
Infinite (%)0.0%
Mean0.08898952574
Minimum0
Maximum6
Zeros33821
Zeros (%)78.7%
Memory size335.8 KiB
2020-11-30T23:56:31.476700image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum6
Range6
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.3959945651
Coefficient of variation (CV)4.449900838
Kurtosis38.07321442
Mean0.08898952574
Median Absolute Deviation (MAD)0
Skewness5.577484144
Sum3203
Variance0.1568116956
MonotocityNot monotonic
2020-11-30T23:56:31.567152image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
03382178.7%
 
113913.2%
 
25931.4%
 
31440.3%
 
4280.1%
 
514< 0.1%
 
62< 0.1%
 
(Missing)696916.2%
 
ValueCountFrequency (%) 
03382178.7%
 
113913.2%
 
25931.4%
 
31440.3%
 
4280.1%
 
514< 0.1%
 
62< 0.1%
 
ValueCountFrequency (%) 
62< 0.1%
 
514< 0.1%
 
4280.1%
 
31440.3%
 
25931.4%
 
113913.2%
 
03382178.7%
 

ANZ_PERSONEN
Real number (ℝ≥0)

MISSING
ZEROS

Distinct14
Distinct (%)< 0.1%
Missing6969
Missing (%)16.2%
Infinite0
Infinite (%)0.0%
Mean2.017086656
Minimum0
Maximum24
Zeros2709
Zeros (%)6.3%
Memory size335.8 KiB
2020-11-30T23:56:31.670612image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q33
95-th percentile5
Maximum24
Range24
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.358095553
Coefficient of variation (CV)0.6732955914
Kurtosis3.649381657
Mean2.017086656
Median Absolute Deviation (MAD)1
Skewness1.198737521
Sum72601
Variance1.84442353
MonotocityNot monotonic
2020-11-30T23:56:31.785338image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%) 
11211828.2%
 
21087025.3%
 
3543712.7%
 
429506.9%
 
027096.3%
 
511932.8%
 
64811.1%
 
71580.4%
 
8460.1%
 
9220.1%
 
105< 0.1%
 
112< 0.1%
 
131< 0.1%
 
241< 0.1%
 
(Missing)696916.2%
 
ValueCountFrequency (%) 
027096.3%
 
11211828.2%
 
21087025.3%
 
3543712.7%
 
429506.9%
 
511932.8%
 
64811.1%
 
71580.4%
 
8460.1%
 
9220.1%
 
ValueCountFrequency (%) 
241< 0.1%
 
131< 0.1%
 
112< 0.1%
 
105< 0.1%
 
9220.1%
 
8460.1%
 
71580.4%
 
64811.1%
 
511932.8%
 
429506.9%
 

ANZ_STATISTISCHE_HAUSHALTE
Real number (ℝ≥0)

MISSING

Distinct173
Distinct (%)0.5%
Missing7777
Missing (%)18.1%
Infinite0
Infinite (%)0.0%
Mean6.275856189
Minimum0
Maximum369
Zeros95
Zeros (%)0.2%
Memory size335.8 KiB
2020-11-30T23:56:31.916539image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median2
Q37
95-th percentile24
Maximum369
Range369
Interquartile range (IQR)6

Descriptive statistics

Standard deviation14.32633307
Coefficient of variation (CV)2.282769497
Kurtosis148.1784167
Mean6.275856189
Median Absolute Deviation (MAD)1
Skewness9.519613815
Sum220816
Variance205.2438193
MonotocityNot monotonic
2020-11-30T23:56:32.047650image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
11478434.4%
 
2539112.5%
 
321074.9%
 
414183.3%
 
613113.1%
 
512803.0%
 
711772.7%
 
810532.5%
 
99182.1%
 
107531.8%
 
115671.3%
 
124751.1%
 
133680.9%
 
143260.8%
 
152130.5%
 
162090.5%
 
171960.5%
 
181760.4%
 
191490.3%
 
201240.3%
 
211020.2%
 
221010.2%
 
0950.2%
 
24940.2%
 
28880.2%
 
Other values (148)17104.0%
 
(Missing)777718.1%
 
ValueCountFrequency (%) 
0950.2%
 
11478434.4%
 
2539112.5%
 
321074.9%
 
414183.3%
 
512803.0%
 
613113.1%
 
711772.7%
 
810532.5%
 
99182.1%
 
ValueCountFrequency (%) 
3691< 0.1%
 
3541< 0.1%
 
3422< 0.1%
 
3392< 0.1%
 
3221< 0.1%
 
3191< 0.1%
 
3043< 0.1%
 
2991< 0.1%
 
2971< 0.1%
 
2741< 0.1%
 

ANZ_TITEL
Categorical

MISSING

Distinct3
Distinct (%)< 0.1%
Missing6969
Missing (%)16.2%
Memory size335.8 KiB
0
35674 
1
 
293
2
 
26
ValueCountFrequency (%) 
03567483.0%
 
12930.7%
 
2260.1%
 
(Missing)696916.2%
 
2020-11-30T23:56:32.194200image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters6
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
07166755.6%
 
.3599327.9%
 
n1393810.8%
 
a69695.4%
 
12930.2%
 
226< 0.1%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number7198655.9%
 
Other Punctuation3599327.9%
 
Lowercase Letter2090716.2%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
07166799.6%
 
12930.4%
 
226< 0.1%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
.35993100.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n1393866.7%
 
a696933.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Common10797983.8%
 
Latin2090716.2%
 

Most frequent Common characters

ValueCountFrequency (%) 
07166766.4%
 
.3599333.3%
 
12930.3%
 
226< 0.1%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n1393866.7%
 
a696933.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII128886100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
07166755.6%
 
.3599327.9%
 
n1393810.8%
 
a69695.4%
 
12930.2%
 
226< 0.1%
 

ARBEIT
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing7951
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean3.045214361
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:56:32.298438image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile4
Maximum9
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.036404283
Coefficient of variation (CV)0.3403386955
Kurtosis-0.4478248745
Mean3.045214361
Median Absolute Deviation (MAD)1
Skewness-0.3506897956
Sum106616
Variance1.074133838
MonotocityNot monotonic
2020-11-30T23:56:32.381744image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
41232328.7%
 
31122326.1%
 
2691016.1%
 
132427.5%
 
513063.0%
 
97< 0.1%
 
(Missing)795118.5%
 
ValueCountFrequency (%) 
132427.5%
 
2691016.1%
 
31122326.1%
 
41232328.7%
 
513063.0%
 
97< 0.1%
 
ValueCountFrequency (%) 
97< 0.1%
 
513063.0%
 
41232328.7%
 
31122326.1%
 
2691016.1%
 
132427.5%
 

BALLRAUM
Real number (ℝ≥0)

MISSING

Distinct7
Distinct (%)< 0.1%
Missing7799
Missing (%)18.2%
Infinite0
Infinite (%)0.0%
Mean4.256775588
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:56:32.468934image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median5
Q36
95-th percentile7
Maximum7
Range6
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.195305614
Coefficient of variation (CV)0.5157203071
Kurtosis-1.483222281
Mean4.256775588
Median Absolute Deviation (MAD)2
Skewness-0.3155678814
Sum149681
Variance4.819366737
MonotocityNot monotonic
2020-11-30T23:56:32.551044image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
61157927.0%
 
1652115.2%
 
7490511.4%
 
2432910.1%
 
329676.9%
 
425185.9%
 
523445.5%
 
(Missing)779918.2%
 
ValueCountFrequency (%) 
1652115.2%
 
2432910.1%
 
329676.9%
 
425185.9%
 
523445.5%
 
61157927.0%
 
7490511.4%
 
ValueCountFrequency (%) 
7490511.4%
 
61157927.0%
 
523445.5%
 
425185.9%
 
329676.9%
 
2432910.1%
 
1652115.2%
 

CAMEO_DEU_2015
Categorical

MISSING

Distinct45
Distinct (%)0.1%
Missing7888
Missing (%)18.4%
Memory size335.8 KiB
6B
 
2452
4C
 
2216
3D
 
2152
2D
 
1991
4A
 
1684
Other values (40)
24579 
ValueCountFrequency (%) 
6B24525.7%
 
4C22165.2%
 
3D21525.0%
 
2D19914.6%
 
4A16843.9%
 
8A15973.7%
 
3C15473.6%
 
8C12672.9%
 
7A12422.9%
 
2C11732.7%
 
8D11682.7%
 
6E11172.6%
 
8B9782.3%
 
2B9422.2%
 
7B8442.0%
 
1D8121.9%
 
5D7871.8%
 
6C7611.8%
 
1A6911.6%
 
9D6691.6%
 
2A5971.4%
 
9B5151.2%
 
4B4811.1%
 
5A4671.1%
 
9A4651.1%
 
Other values (20)645915.0%
 
(Missing)788818.4%
 
2020-11-30T23:56:32.685225image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters18
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
n1577616.8%
 
D86149.2%
 
C85089.1%
 
a78888.4%
 
A73427.8%
 
B72307.7%
 
653635.7%
 
451315.5%
 
850105.3%
 
247035.0%
 
344234.7%
 
730643.3%
 
E27302.9%
 
525312.7%
 
924602.6%
 
123782.5%
 
F6390.7%
 
X22< 0.1%
 

Most occurring categories

ValueCountFrequency (%) 
Uppercase Letter3508537.4%
 
Decimal Number3506337.4%
 
Lowercase Letter2366425.2%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
6536315.3%
 
4513114.6%
 
8501014.3%
 
2470313.4%
 
3442312.6%
 
730648.7%
 
525317.2%
 
924607.0%
 
123786.8%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
D861424.6%
 
C850824.2%
 
A734220.9%
 
B723020.6%
 
E27307.8%
 
F6391.8%
 
X220.1%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n1577666.7%
 
a788833.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin5874962.6%
 
Common3506337.4%
 

Most frequent Common characters

ValueCountFrequency (%) 
6536315.3%
 
4513114.6%
 
8501014.3%
 
2470313.4%
 
3442312.6%
 
730648.7%
 
525317.2%
 
924607.0%
 
123786.8%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n1577626.9%
 
D861414.7%
 
C850814.5%
 
a788813.4%
 
A734212.5%
 
B723012.3%
 
E27304.6%
 
F6391.1%
 
X22< 0.1%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII93812100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
n1577616.8%
 
D86149.2%
 
C85089.1%
 
a78888.4%
 
A73427.8%
 
B72307.7%
 
653635.7%
 
451315.5%
 
850105.3%
 
247035.0%
 
344234.7%
 
730643.3%
 
E27302.9%
 
525312.7%
 
924602.6%
 
123782.5%
 
F6390.7%
 
X22< 0.1%
 

CAMEO_DEUG_2015
Real number (ℝ≥0)

MISSING

Distinct9
Distinct (%)< 0.1%
Missing7899
Missing (%)18.4%
Infinite0
Infinite (%)0.0%
Mean4.964720646
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:56:32.823281image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median5
Q37
95-th percentile9
Maximum9
Range8
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.419329681
Coefficient of variation (CV)0.4873042924
Kurtosis-1.203828175
Mean4.964720646
Median Absolute Deviation (MAD)2
Skewness0.04958759269
Sum174078
Variance5.853156107
MonotocityNot monotonic
2020-11-30T23:56:32.917146image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%) 
6536312.5%
 
4513111.9%
 
8501011.7%
 
2470310.9%
 
3442310.3%
 
730647.1%
 
525315.9%
 
924605.7%
 
123785.5%
 
(Missing)789918.4%
 
ValueCountFrequency (%) 
123785.5%
 
2470310.9%
 
3442310.3%
 
4513111.9%
 
525315.9%
 
6536312.5%
 
730647.1%
 
8501011.7%
 
924605.7%
 
ValueCountFrequency (%) 
924605.7%
 
8501011.7%
 
730647.1%
 
6536312.5%
 
525315.9%
 
4513111.9%
 
3442310.3%
 
2470310.9%
 
123785.5%
 

CAMEO_INTL_2015
Real number (ℝ≥0)

MISSING

Distinct21
Distinct (%)0.1%
Missing7899
Missing (%)18.4%
Infinite0
Infinite (%)0.0%
Mean32.88483587
Minimum12
Maximum55
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:56:33.028842image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum12
5-th percentile13
Q123
median32
Q345
95-th percentile54
Maximum55
Range43
Interquartile range (IQR)22

Descriptive statistics

Standard deviation14.16654623
Coefficient of variation (CV)0.4307926695
Kurtosis-1.395326926
Mean32.88483587
Median Absolute Deviation (MAD)11
Skewness0.07937703955
Sum1153041
Variance200.6910321
MonotocityNot monotonic
2020-11-30T23:56:33.137635image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%) 
2442109.8%
 
1436748.6%
 
5132147.5%
 
4130647.1%
 
2524555.7%
 
4324525.7%
 
4519064.4%
 
5418564.3%
 
2216843.9%
 
1316333.8%
 
5515463.6%
 
2312052.8%
 
1511772.7%
 
349652.2%
 
447611.8%
 
317251.7%
 
356141.4%
 
125971.4%
 
524651.1%
 
324381.0%
 
334221.0%
 
(Missing)789918.4%
 
ValueCountFrequency (%) 
125971.4%
 
1316333.8%
 
1436748.6%
 
1511772.7%
 
2216843.9%
 
2312052.8%
 
2442109.8%
 
2524555.7%
 
317251.7%
 
324381.0%
 
ValueCountFrequency (%) 
5515463.6%
 
5418564.3%
 
524651.1%
 
5132147.5%
 
4519064.4%
 
447611.8%
 
4324525.7%
 
4130647.1%
 
356141.4%
 
349652.2%
 

CJT_GESAMTTYP
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing605
Missing (%)1.4%
Infinite0
Infinite (%)0.0%
Mean3.314233775
Minimum1
Maximum6
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:56:33.230066image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q35
95-th percentile6
Maximum6
Range5
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.775396833
Coefficient of variation (CV)0.5356884738
Kurtosis-1.330734723
Mean3.314233775
Median Absolute Deviation (MAD)1
Skewness0.3074453671
Sum140381
Variance3.152033914
MonotocityNot monotonic
2020-11-30T23:56:33.318977image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
21281329.8%
 
6842919.6%
 
1667115.5%
 
4602414.0%
 
3434310.1%
 
540779.5%
 
(Missing)6051.4%
 
ValueCountFrequency (%) 
1667115.5%
 
21281329.8%
 
3434310.1%
 
4602414.0%
 
540779.5%
 
6842919.6%
 
ValueCountFrequency (%) 
6842919.6%
 
540779.5%
 
4602414.0%
 
3434310.1%
 
21281329.8%
 
1667115.5%
 

CJT_KATALOGNUTZER
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing605
Missing (%)1.4%
Infinite0
Infinite (%)0.0%
Mean3.89623911
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:56:33.402882image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median5
Q35
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.442273638
Coefficient of variation (CV)0.3701707202
Kurtosis-0.4793156977
Mean3.89623911
Median Absolute Deviation (MAD)0
Skewness-0.9907699111
Sum165033
Variance2.080153246
MonotocityNot monotonic
2020-11-30T23:56:33.494676image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
52281353.1%
 
4604914.1%
 
1555812.9%
 
3534012.4%
 
225976.0%
 
(Missing)6051.4%
 
ValueCountFrequency (%) 
1555812.9%
 
225976.0%
 
3534012.4%
 
4604914.1%
 
52281353.1%
 
ValueCountFrequency (%) 
52281353.1%
 
4604914.1%
 
3534012.4%
 
225976.0%
 
1555812.9%
 

CJT_TYP_1
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing605
Missing (%)1.4%
Infinite0
Infinite (%)0.0%
Mean2.541020374
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:56:33.604740image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median2
Q33
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.35457568
Coefficient of variation (CV)0.5330833605
Kurtosis-0.6801481373
Mean2.541020374
Median Absolute Deviation (MAD)1
Skewness0.7464753142
Sum107630
Variance1.834875274
MonotocityNot monotonic
2020-11-30T23:56:33.700820image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
21752640.8%
 
1942421.9%
 
5724316.9%
 
3571713.3%
 
424475.7%
 
(Missing)6051.4%
 
ValueCountFrequency (%) 
1942421.9%
 
21752640.8%
 
3571713.3%
 
424475.7%
 
5724316.9%
 
ValueCountFrequency (%) 
5724316.9%
 
424475.7%
 
3571713.3%
 
21752640.8%
 
1942421.9%
 

CJT_TYP_2
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing605
Missing (%)1.4%
Infinite0
Infinite (%)0.0%
Mean2.313501901
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:56:33.795449image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q33
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.394950693
Coefficient of variation (CV)0.6029606861
Kurtosis-0.4830485624
Mean2.313501901
Median Absolute Deviation (MAD)1
Skewness0.9045024402
Sum97993
Variance1.945887437
MonotocityNot monotonic
2020-11-30T23:56:33.881460image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
11495634.8%
 
21430333.3%
 
5655915.3%
 
3452010.5%
 
420194.7%
 
(Missing)6051.4%
 
ValueCountFrequency (%) 
11495634.8%
 
21430333.3%
 
3452010.5%
 
420194.7%
 
5655915.3%
 
ValueCountFrequency (%) 
5655915.3%
 
420194.7%
 
3452010.5%
 
21430333.3%
 
11495634.8%
 

CJT_TYP_3
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing605
Missing (%)1.4%
Infinite0
Infinite (%)0.0%
Mean4.473074108
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:56:33.976009image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q14
median5
Q35
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9264752221
Coefficient of variation (CV)0.2071227079
Kurtosis2.557497023
Mean4.473074108
Median Absolute Deviation (MAD)0
Skewness-1.808882593
Sum189466
Variance0.8583563372
MonotocityNot monotonic
2020-11-30T23:56:34.059682image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
52935168.3%
 
4671815.6%
 
338248.9%
 
219034.4%
 
15611.3%
 
(Missing)6051.4%
 
ValueCountFrequency (%) 
15611.3%
 
219034.4%
 
338248.9%
 
4671815.6%
 
52935168.3%
 
ValueCountFrequency (%) 
52935168.3%
 
4671815.6%
 
338248.9%
 
219034.4%
 
15611.3%
 

CJT_TYP_4
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing605
Missing (%)1.4%
Infinite0
Infinite (%)0.0%
Mean4.377151356
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:56:34.149252image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q14
median5
Q35
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.063100387
Coefficient of variation (CV)0.2428749431
Kurtosis1.883901004
Mean4.377151356
Median Absolute Deviation (MAD)0
Skewness-1.701534233
Sum185403
Variance1.130182432
MonotocityNot monotonic
2020-11-30T23:56:34.229948image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
52846166.2%
 
4667015.5%
 
331807.4%
 
228326.6%
 
112142.8%
 
(Missing)6051.4%
 
ValueCountFrequency (%) 
112142.8%
 
228326.6%
 
331807.4%
 
4667015.5%
 
52846166.2%
 
ValueCountFrequency (%) 
52846166.2%
 
4667015.5%
 
331807.4%
 
228326.6%
 
112142.8%
 

CJT_TYP_5
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing605
Missing (%)1.4%
Infinite0
Infinite (%)0.0%
Mean4.464999882
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:56:34.317774image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q14
median5
Q35
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9450299226
Coefficient of variation (CV)0.2116528438
Kurtosis2.500169343
Mean4.464999882
Median Absolute Deviation (MAD)0
Skewness-1.789106007
Sum189124
Variance0.8930815546
MonotocityNot monotonic
2020-11-30T23:56:34.402709image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
52964069.0%
 
4573813.4%
 
3475011.1%
 
214933.5%
 
17361.7%
 
(Missing)6051.4%
 
ValueCountFrequency (%) 
17361.7%
 
214933.5%
 
3475011.1%
 
4573813.4%
 
52964069.0%
 
ValueCountFrequency (%) 
52964069.0%
 
4573813.4%
 
3475011.1%
 
214933.5%
 
17361.7%
 

CJT_TYP_6
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing605
Missing (%)1.4%
Infinite0
Infinite (%)0.0%
Mean4.424581533
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:56:34.500954image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q14
median5
Q35
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9810789739
Coefficient of variation (CV)0.2217337316
Kurtosis2.148161595
Mean4.424581533
Median Absolute Deviation (MAD)0
Skewness-1.733724201
Sum187412
Variance0.9625159531
MonotocityNot monotonic
2020-11-30T23:56:34.589691image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
52854366.4%
 
4719816.8%
 
333817.9%
 
225275.9%
 
17081.6%
 
(Missing)6051.4%
 
ValueCountFrequency (%) 
17081.6%
 
225275.9%
 
333817.9%
 
4719816.8%
 
52854366.4%
 
ValueCountFrequency (%) 
52854366.4%
 
4719816.8%
 
333817.9%
 
225275.9%
 
17081.6%
 

D19_BANKEN_ANZ_12
Real number (ℝ≥0)

ZEROS

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1017177971
Minimum0
Maximum6
Zeros40198
Zeros (%)93.6%
Memory size335.8 KiB
2020-11-30T23:56:34.683096image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum6
Range6
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.4540652053
Coefficient of variation (CV)4.463970103
Kurtosis43.06699646
Mean0.1017177971
Median Absolute Deviation (MAD)0
Skewness5.920366395
Sum4370
Variance0.2061752107
MonotocityNot monotonic
2020-11-30T23:56:34.764807image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
04019893.6%
 
117264.0%
 
26931.6%
 
31800.4%
 
41180.3%
 
5360.1%
 
611< 0.1%
 
ValueCountFrequency (%) 
04019893.6%
 
117264.0%
 
26931.6%
 
31800.4%
 
41180.3%
 
5360.1%
 
611< 0.1%
 
ValueCountFrequency (%) 
611< 0.1%
 
5360.1%
 
41180.3%
 
31800.4%
 
26931.6%
 
117264.0%
 
04019893.6%
 

D19_BANKEN_ANZ_24
Real number (ℝ≥0)

ZEROS

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1760625669
Minimum0
Maximum6
Zeros38714
Zeros (%)90.1%
Memory size335.8 KiB
2020-11-30T23:56:34.851043image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum6
Range6
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.6328577229
Coefficient of variation (CV)3.594504692
Kurtosis25.07695609
Mean0.1760625669
Median Absolute Deviation (MAD)0
Skewness4.635247071
Sum7564
Variance0.4005088975
MonotocityNot monotonic
2020-11-30T23:56:34.933904image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
03871490.1%
 
123045.4%
 
211622.7%
 
33620.8%
 
42890.7%
 
5920.2%
 
6390.1%
 
ValueCountFrequency (%) 
03871490.1%
 
123045.4%
 
211622.7%
 
33620.8%
 
42890.7%
 
5920.2%
 
6390.1%
 
ValueCountFrequency (%) 
6390.1%
 
5920.2%
 
42890.7%
 
33620.8%
 
211622.7%
 
123045.4%
 
03871490.1%
 

D19_BANKEN_DATUM
Real number (ℝ≥0)

Distinct10
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.352776873
Minimum1
Maximum10
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:56:35.023920image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5
Q110
median10
Q310
95-th percentile10
Maximum10
Range9
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.630258688
Coefficient of variation (CV)0.1743074501
Kurtosis9.031150149
Mean9.352776873
Median Absolute Deviation (MAD)0
Skewness-3.002569089
Sum401814
Variance2.657743389
MonotocityNot monotonic
2020-11-30T23:56:35.105227image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
103391378.9%
 
935048.2%
 
517064.0%
 
812973.0%
 
78051.9%
 
66791.6%
 
13420.8%
 
42920.7%
 
22490.6%
 
31750.4%
 
ValueCountFrequency (%) 
13420.8%
 
22490.6%
 
31750.4%
 
42920.7%
 
517064.0%
 
66791.6%
 
78051.9%
 
812973.0%
 
935048.2%
 
103391378.9%
 
ValueCountFrequency (%) 
103391378.9%
 
935048.2%
 
812973.0%
 
78051.9%
 
66791.6%
 
517064.0%
 
42920.7%
 
31750.4%
 
22490.6%
 
13420.8%
 

D19_BANKEN_DIREKT
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.7028304083
Minimum0
Maximum7
Zeros36805
Zeros (%)85.7%
Memory size335.8 KiB
2020-11-30T23:56:35.187650image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile6
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.818202309
Coefficient of variation (CV)2.586971604
Kurtosis4.007649091
Mean0.7028304083
Median Absolute Deviation (MAD)0
Skewness2.381729213
Sum30195
Variance3.305859636
MonotocityNot monotonic
2020-11-30T23:56:35.269795image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
03680585.7%
 
631197.3%
 
312322.9%
 
57301.7%
 
73230.8%
 
22810.7%
 
42800.7%
 
11920.4%
 
ValueCountFrequency (%) 
03680585.7%
 
11920.4%
 
22810.7%
 
312322.9%
 
42800.7%
 
57301.7%
 
631197.3%
 
73230.8%
 
ValueCountFrequency (%) 
73230.8%
 
631197.3%
 
57301.7%
 
42800.7%
 
312322.9%
 
22810.7%
 
11920.4%
 
03680585.7%
 

D19_BANKEN_GROSS
Real number (ℝ≥0)

ZEROS

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.4633629719
Minimum0
Maximum6
Zeros38760
Zeros (%)90.2%
Memory size335.8 KiB
2020-11-30T23:56:35.357704image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile5
Maximum6
Range6
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.488132905
Coefficient of variation (CV)3.211592197
Kurtosis8.087930639
Mean0.4633629719
Median Absolute Deviation (MAD)0
Skewness3.106387172
Sum19907
Variance2.214539543
MonotocityNot monotonic
2020-11-30T23:56:35.438093image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
03876090.2%
 
621385.0%
 
38532.0%
 
55861.4%
 
42580.6%
 
21910.4%
 
11760.4%
 
ValueCountFrequency (%) 
03876090.2%
 
11760.4%
 
21910.4%
 
38532.0%
 
42580.6%
 
55861.4%
 
621385.0%
 
ValueCountFrequency (%) 
621385.0%
 
55861.4%
 
42580.6%
 
38532.0%
 
21910.4%
 
11760.4%
 
03876090.2%
 

D19_BANKEN_LOKAL
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1043945813
Minimum0
Maximum7
Zeros42170
Zeros (%)98.2%
Memory size335.8 KiB
2020-11-30T23:56:35.524759image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.7940971665
Coefficient of variation (CV)7.606689514
Kurtosis61.27084897
Mean0.1043945813
Median Absolute Deviation (MAD)0
Skewness7.845757537
Sum4485
Variance0.6305903099
MonotocityNot monotonic
2020-11-30T23:56:35.607969image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
04217098.2%
 
73670.9%
 
61950.5%
 
31820.4%
 
5320.1%
 
29< 0.1%
 
45< 0.1%
 
12< 0.1%
 
ValueCountFrequency (%) 
04217098.2%
 
12< 0.1%
 
29< 0.1%
 
31820.4%
 
45< 0.1%
 
5320.1%
 
61950.5%
 
73670.9%
 
ValueCountFrequency (%) 
73670.9%
 
61950.5%
 
5320.1%
 
45< 0.1%
 
31820.4%
 
29< 0.1%
 
12< 0.1%
 
04217098.2%
 

D19_BANKEN_OFFLINE_DATUM
Real number (ℝ≥0)

Distinct10
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.851799264
Minimum1
Maximum10
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:56:35.700824image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile10
Q110
median10
Q310
95-th percentile10
Maximum10
Range9
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.8212257993
Coefficient of variation (CV)0.08335795089
Kurtosis39.03040409
Mean9.851799264
Median Absolute Deviation (MAD)0
Skewness-6.118856861
Sum423253
Variance0.6744118134
MonotocityNot monotonic
2020-11-30T23:56:35.782663image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
104125896.0%
 
58492.0%
 
84431.0%
 
92500.6%
 
6610.1%
 
2550.1%
 
416< 0.1%
 
114< 0.1%
 
78< 0.1%
 
38< 0.1%
 
ValueCountFrequency (%) 
114< 0.1%
 
2550.1%
 
38< 0.1%
 
416< 0.1%
 
58492.0%
 
6610.1%
 
78< 0.1%
 
84431.0%
 
92500.6%
 
104125896.0%
 
ValueCountFrequency (%) 
104125896.0%
 
92500.6%
 
84431.0%
 
78< 0.1%
 
6610.1%
 
58492.0%
 
416< 0.1%
 
38< 0.1%
 
2550.1%
 
114< 0.1%
 

D19_BANKEN_ONLINE_DATUM
Real number (ℝ≥0)

Distinct10
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.579698338
Minimum1
Maximum10
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:56:35.870485image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile7
Q110
median10
Q310
95-th percentile10
Maximum10
Range9
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.359768472
Coefficient of variation (CV)0.1419427234
Kurtosis17.49548611
Mean9.579698338
Median Absolute Deviation (MAD)0
Skewness-4.051365088
Sum411563
Variance1.848970296
MonotocityNot monotonic
2020-11-30T23:56:35.952290image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
103691585.9%
 
925616.0%
 
57871.8%
 
87621.8%
 
76281.5%
 
65051.2%
 
12900.7%
 
42280.5%
 
21530.4%
 
31330.3%
 
ValueCountFrequency (%) 
12900.7%
 
21530.4%
 
31330.3%
 
42280.5%
 
57871.8%
 
65051.2%
 
76281.5%
 
87621.8%
 
925616.0%
 
103691585.9%
 
ValueCountFrequency (%) 
103691585.9%
 
925616.0%
 
87621.8%
 
76281.5%
 
65051.2%
 
57871.8%
 
42280.5%
 
31330.3%
 
21530.4%
 
12900.7%
 

D19_BANKEN_ONLINE_QUOTE_12
Real number (ℝ≥0)

MISSING
ZEROS

Distinct8
Distinct (%)< 0.1%
Missing7584
Missing (%)17.7%
Infinite0
Infinite (%)0.0%
Mean0.4374187348
Minimum0
Maximum10
Zeros33787
Zeros (%)78.6%
Memory size335.8 KiB
2020-11-30T23:56:36.036421image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum10
Range10
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.029657884
Coefficient of variation (CV)4.64007991
Kurtosis17.93882446
Mean0.4374187348
Median Absolute Deviation (MAD)0
Skewness4.456240551
Sum15475
Variance4.119511125
MonotocityNot monotonic
2020-11-30T23:56:36.122979image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
03378778.6%
 
1014833.5%
 
5420.1%
 
7250.1%
 
818< 0.1%
 
314< 0.1%
 
98< 0.1%
 
21< 0.1%
 
(Missing)758417.7%
 
ValueCountFrequency (%) 
03378778.6%
 
21< 0.1%
 
314< 0.1%
 
5420.1%
 
7250.1%
 
818< 0.1%
 
98< 0.1%
 
1014833.5%
 
ValueCountFrequency (%) 
1014833.5%
 
98< 0.1%
 
818< 0.1%
 
7250.1%
 
5420.1%
 
314< 0.1%
 
21< 0.1%
 
03378778.6%
 

D19_BANKEN_REST
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.3760532564
Minimum0
Maximum7
Zeros39983
Zeros (%)93.1%
Memory size335.8 KiB
2020-11-30T23:56:36.206391image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile5
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.416897856
Coefficient of variation (CV)3.767811692
Kurtosis11.42658949
Mean0.3760532564
Median Absolute Deviation (MAD)0
Skewness3.623033168
Sum16156
Variance2.007599534
MonotocityNot monotonic
2020-11-30T23:56:36.289010image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
03998393.1%
 
619564.6%
 
53570.8%
 
33400.8%
 
71840.4%
 
2800.2%
 
4350.1%
 
1270.1%
 
ValueCountFrequency (%) 
03998393.1%
 
1270.1%
 
2800.2%
 
33400.8%
 
4350.1%
 
53570.8%
 
619564.6%
 
71840.4%
 
ValueCountFrequency (%) 
71840.4%
 
619564.6%
 
53570.8%
 
4350.1%
 
33400.8%
 
2800.2%
 
1270.1%
 
03998393.1%
 

D19_BEKLEIDUNG_GEH
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.8254736744
Minimum0
Maximum7
Zeros35949
Zeros (%)83.7%
Memory size335.8 KiB
2020-11-30T23:56:36.378592image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile6
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.962660932
Coefficient of variation (CV)2.377617836
Kurtosis2.752862429
Mean0.8254736744
Median Absolute Deviation (MAD)0
Skewness2.113969372
Sum35464
Variance3.852037932
MonotocityNot monotonic
2020-11-30T23:56:36.460441image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
03594983.7%
 
634968.1%
 
314423.4%
 
510652.5%
 
75321.2%
 
22090.5%
 
41420.3%
 
11270.3%
 
ValueCountFrequency (%) 
03594983.7%
 
11270.3%
 
22090.5%
 
314423.4%
 
41420.3%
 
510652.5%
 
634968.1%
 
75321.2%
 
ValueCountFrequency (%) 
75321.2%
 
634968.1%
 
510652.5%
 
41420.3%
 
314423.4%
 
22090.5%
 
11270.3%
 
03594983.7%
 

D19_BEKLEIDUNG_REST
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.655113822
Minimum0
Maximum7
Zeros29981
Zeros (%)69.8%
Memory size335.8 KiB
2020-11-30T23:56:36.548720image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q34
95-th percentile6
Maximum7
Range7
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.634217798
Coefficient of variation (CV)1.591562927
Kurtosis-0.7262049921
Mean1.655113822
Median Absolute Deviation (MAD)0
Skewness1.065971234
Sum71107
Variance6.939103408
MonotocityNot monotonic
2020-11-30T23:56:36.628408image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
02998169.8%
 
6769017.9%
 
719754.6%
 
316453.8%
 
59212.1%
 
23270.8%
 
12480.6%
 
41750.4%
 
ValueCountFrequency (%) 
02998169.8%
 
12480.6%
 
23270.8%
 
316453.8%
 
41750.4%
 
59212.1%
 
6769017.9%
 
719754.6%
 
ValueCountFrequency (%) 
719754.6%
 
6769017.9%
 
59212.1%
 
41750.4%
 
316453.8%
 
23270.8%
 
12480.6%
 
02998169.8%
 

D19_BILDUNG
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.017201248
Minimum0
Maximum7
Zeros34895
Zeros (%)81.2%
Memory size335.8 KiB
2020-11-30T23:56:36.714482image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile6
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.23234489
Coefficient of variation (CV)2.194595116
Kurtosis1.687023278
Mean1.017201248
Median Absolute Deviation (MAD)0
Skewness1.870464198
Sum43701
Variance4.983363708
MonotocityNot monotonic
2020-11-30T23:56:36.796821image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
03489581.2%
 
642499.9%
 
717414.1%
 
29152.1%
 
35841.4%
 
53690.9%
 
41280.3%
 
1810.2%
 
ValueCountFrequency (%) 
03489581.2%
 
1810.2%
 
29152.1%
 
35841.4%
 
41280.3%
 
53690.9%
 
642499.9%
 
717414.1%
 
ValueCountFrequency (%) 
717414.1%
 
642499.9%
 
53690.9%
 
41280.3%
 
35841.4%
 
29152.1%
 
1810.2%
 
03489581.2%
 

D19_BIO_OEKO
Real number (ℝ≥0)

ZEROS

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.63658582
Minimum0
Maximum7
Zeros38422
Zeros (%)89.4%
Memory size335.8 KiB
2020-11-30T23:56:36.883675image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile6
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.875460819
Coefficient of variation (CV)2.946124089
Kurtosis5.224113502
Mean0.63658582
Median Absolute Deviation (MAD)0
Skewness2.66208952
Sum27349
Variance3.517353283
MonotocityNot monotonic
2020-11-30T23:56:36.968627image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
03842289.4%
 
628696.7%
 
711522.7%
 
52550.6%
 
32520.6%
 
48< 0.1%
 
24< 0.1%
 
ValueCountFrequency (%) 
03842289.4%
 
24< 0.1%
 
32520.6%
 
48< 0.1%
 
52550.6%
 
628696.7%
 
711522.7%
 
ValueCountFrequency (%) 
711522.7%
 
628696.7%
 
52550.6%
 
48< 0.1%
 
32520.6%
 
24< 0.1%
 
03842289.4%
 

D19_BUCH_CD
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.526721289
Minimum0
Maximum7
Zeros22410
Zeros (%)52.2%
Memory size335.8 KiB
2020-11-30T23:56:37.058145image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q36
95-th percentile6
Maximum7
Range7
Interquartile range (IQR)6

Descriptive statistics

Standard deviation2.837579407
Coefficient of variation (CV)1.123028258
Kurtosis-1.77898207
Mean2.526721289
Median Absolute Deviation (MAD)0
Skewness0.3414315952
Sum108553
Variance8.051856893
MonotocityNot monotonic
2020-11-30T23:56:37.134935image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
02241052.2%
 
61459234.0%
 
317274.0%
 
511322.6%
 
110542.5%
 
77821.8%
 
27141.7%
 
45511.3%
 
ValueCountFrequency (%) 
02241052.2%
 
110542.5%
 
27141.7%
 
317274.0%
 
45511.3%
 
511322.6%
 
61459234.0%
 
77821.8%
 
ValueCountFrequency (%) 
77821.8%
 
61459234.0%
 
511322.6%
 
45511.3%
 
317274.0%
 
27141.7%
 
110542.5%
 
02241052.2%
 

D19_DIGIT_SERV
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1995018854
Minimum0
Maximum7
Zeros41226
Zeros (%)96.0%
Memory size335.8 KiB
2020-11-30T23:56:37.219581image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.019639885
Coefficient of variation (CV)5.110928566
Kurtosis26.23316305
Mean0.1995018854
Median Absolute Deviation (MAD)0
Skewness5.216089215
Sum8571
Variance1.039665495
MonotocityNot monotonic
2020-11-30T23:56:37.303888image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
04122696.0%
 
68902.1%
 
34311.0%
 
51890.4%
 
71010.2%
 
2740.2%
 
4290.1%
 
1220.1%
 
ValueCountFrequency (%) 
04122696.0%
 
1220.1%
 
2740.2%
 
34311.0%
 
4290.1%
 
51890.4%
 
68902.1%
 
71010.2%
 
ValueCountFrequency (%) 
71010.2%
 
68902.1%
 
51890.4%
 
4290.1%
 
34311.0%
 
2740.2%
 
1220.1%
 
04122696.0%
 

D19_DROGERIEARTIKEL
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.6809273311
Minimum0
Maximum7
Zeros36725
Zeros (%)85.5%
Memory size335.8 KiB
2020-11-30T23:56:37.393381image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile6
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.769576723
Coefficient of variation (CV)2.598774704
Kurtosis4.396707696
Mean0.6809273311
Median Absolute Deviation (MAD)0
Skewness2.440765157
Sum29254
Variance3.13140178
MonotocityNot monotonic
2020-11-30T23:56:37.475501image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
03672585.5%
 
625065.8%
 
312723.0%
 
58852.1%
 
44461.0%
 
74401.0%
 
24251.0%
 
12630.6%
 
ValueCountFrequency (%) 
03672585.5%
 
12630.6%
 
24251.0%
 
312723.0%
 
44461.0%
 
58852.1%
 
625065.8%
 
74401.0%
 
ValueCountFrequency (%) 
74401.0%
 
625065.8%
 
58852.1%
 
44461.0%
 
312723.0%
 
24251.0%
 
12630.6%
 
03672585.5%
 

D19_ENERGIE
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.4239095014
Minimum0
Maximum7
Zeros39064
Zeros (%)90.9%
Memory size335.8 KiB
2020-11-30T23:56:37.565385image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile5
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.427791147
Coefficient of variation (CV)3.368150849
Kurtosis10.14904865
Mean0.4239095014
Median Absolute Deviation (MAD)0
Skewness3.371500035
Sum18212
Variance2.03858756
MonotocityNot monotonic
2020-11-30T23:56:37.650798image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
03906490.9%
 
613263.1%
 
312442.9%
 
55971.4%
 
73910.9%
 
21830.4%
 
4930.2%
 
1640.1%
 
ValueCountFrequency (%) 
03906490.9%
 
1640.1%
 
21830.4%
 
312442.9%
 
4930.2%
 
55971.4%
 
613263.1%
 
73910.9%
 
ValueCountFrequency (%) 
73910.9%
 
613263.1%
 
55971.4%
 
4930.2%
 
312442.9%
 
21830.4%
 
1640.1%
 
03906490.9%
 

D19_FREIZEIT
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.614566361
Minimum0
Maximum7
Zeros37678
Zeros (%)87.7%
Memory size335.8 KiB
2020-11-30T23:56:37.741264image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile6
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.718502466
Coefficient of variation (CV)2.796284624
Kurtosis5.160339918
Mean0.614566361
Median Absolute Deviation (MAD)0
Skewness2.610124421
Sum26403
Variance2.953250724
MonotocityNot monotonic
2020-11-30T23:56:37.823340image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
03767887.7%
 
627576.4%
 
311312.6%
 
57431.7%
 
72410.6%
 
21980.5%
 
41520.4%
 
1620.1%
 
ValueCountFrequency (%) 
03767887.7%
 
1620.1%
 
21980.5%
 
311312.6%
 
41520.4%
 
57431.7%
 
627576.4%
 
72410.6%
 
ValueCountFrequency (%) 
72410.6%
 
627576.4%
 
57431.7%
 
41520.4%
 
311312.6%
 
21980.5%
 
1620.1%
 
03767887.7%
 

D19_GARTEN
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.4072436106
Minimum0
Maximum7
Zeros39737
Zeros (%)92.5%
Memory size335.8 KiB
2020-11-30T23:56:37.913832image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile6
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.468958035
Coefficient of variation (CV)3.60707448
Kurtosis10.30109182
Mean0.4072436106
Median Absolute Deviation (MAD)0
Skewness3.458731118
Sum17496
Variance2.157837708
MonotocityNot monotonic
2020-11-30T23:56:37.999130image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
03973792.5%
 
618874.4%
 
54921.1%
 
34501.0%
 
73000.7%
 
2450.1%
 
4410.1%
 
110< 0.1%
 
ValueCountFrequency (%) 
03973792.5%
 
110< 0.1%
 
2450.1%
 
34501.0%
 
4410.1%
 
54921.1%
 
618874.4%
 
73000.7%
 
ValueCountFrequency (%) 
73000.7%
 
618874.4%
 
54921.1%
 
4410.1%
 
34501.0%
 
2450.1%
 
110< 0.1%
 
03973792.5%
 

D19_GESAMT_ANZ_12
Real number (ℝ≥0)

ZEROS

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.9556119361
Minimum0
Maximum6
Zeros25341
Zeros (%)59.0%
Memory size335.8 KiB
2020-11-30T23:56:38.089102image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile4
Maximum6
Range6
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.42541379
Coefficient of variation (CV)1.491624096
Kurtosis1.222362458
Mean0.9556119361
Median Absolute Deviation (MAD)0
Skewness1.466870058
Sum41055
Variance2.031804473
MonotocityNot monotonic
2020-11-30T23:56:38.165064image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
02534159.0%
 
1609614.2%
 
2514512.0%
 
425485.9%
 
324655.7%
 
511202.6%
 
62470.6%
 
ValueCountFrequency (%) 
02534159.0%
 
1609614.2%
 
2514512.0%
 
324655.7%
 
425485.9%
 
511202.6%
 
62470.6%
 
ValueCountFrequency (%) 
62470.6%
 
511202.6%
 
425485.9%
 
324655.7%
 
2514512.0%
 
1609614.2%
 
02534159.0%
 

D19_GESAMT_ANZ_24
Real number (ℝ≥0)

ZEROS

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.445323774
Minimum0
Maximum6
Zeros20736
Zeros (%)48.3%
Memory size335.8 KiB
2020-11-30T23:56:38.246769image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q33
95-th percentile5
Maximum6
Range6
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.771810917
Coefficient of variation (CV)1.225892045
Kurtosis-0.2367616882
Mean1.445323774
Median Absolute Deviation (MAD)1
Skewness0.987304502
Sum62094
Variance3.139313925
MonotocityNot monotonic
2020-11-30T23:56:38.327206image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
02073648.3%
 
2602614.0%
 
1544912.7%
 
438358.9%
 
332337.5%
 
525445.9%
 
611392.7%
 
ValueCountFrequency (%) 
02073648.3%
 
1544912.7%
 
2602614.0%
 
332337.5%
 
438358.9%
 
525445.9%
 
611392.7%
 
ValueCountFrequency (%) 
611392.7%
 
525445.9%
 
438358.9%
 
332337.5%
 
2602614.0%
 
1544912.7%
 
02073648.3%
 

D19_GESAMT_DATUM
Real number (ℝ≥0)

Distinct10
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.547530376
Minimum1
Maximum10
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:56:38.416851image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14
median7
Q310
95-th percentile10
Maximum10
Range9
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.170354825
Coefficient of variation (CV)0.4842062034
Kurtosis-1.25728655
Mean6.547530376
Median Absolute Deviation (MAD)3
Skewness-0.4031662872
Sum281295
Variance10.05114972
MonotocityNot monotonic
2020-11-30T23:56:38.495862image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
101203128.0%
 
5584613.6%
 
9582913.6%
 
139449.2%
 
233867.9%
 
828766.7%
 
625015.8%
 
425015.8%
 
721044.9%
 
319444.5%
 
ValueCountFrequency (%) 
139449.2%
 
233867.9%
 
319444.5%
 
425015.8%
 
5584613.6%
 
625015.8%
 
721044.9%
 
828766.7%
 
9582913.6%
 
101203128.0%
 
ValueCountFrequency (%) 
101203128.0%
 
9582913.6%
 
828766.7%
 
721044.9%
 
625015.8%
 
5584613.6%
 
425015.8%
 
319444.5%
 
233867.9%
 
139449.2%
 

D19_GESAMT_OFFLINE_DATUM
Real number (ℝ≥0)

Distinct10
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.237349285
Minimum1
Maximum10
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:56:38.581656image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q17
median9
Q310
95-th percentile10
Maximum10
Range9
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.292575121
Coefficient of variation (CV)0.2783146667
Kurtosis1.112848068
Mean8.237349285
Median Absolute Deviation (MAD)1
Skewness-1.404995523
Sum353893
Variance5.255900685
MonotocityNot monotonic
2020-11-30T23:56:38.662413image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
101806442.0%
 
9953222.2%
 
842579.9%
 
540019.3%
 
720424.8%
 
617914.2%
 
29992.3%
 
49362.2%
 
16991.6%
 
36411.5%
 
ValueCountFrequency (%) 
16991.6%
 
29992.3%
 
36411.5%
 
49362.2%
 
540019.3%
 
617914.2%
 
720424.8%
 
842579.9%
 
9953222.2%
 
101806442.0%
 
ValueCountFrequency (%) 
101806442.0%
 
9953222.2%
 
842579.9%
 
720424.8%
 
617914.2%
 
540019.3%
 
49362.2%
 
36411.5%
 
29992.3%
 
16991.6%
 

D19_GESAMT_ONLINE_DATUM
Real number (ℝ≥0)

Distinct10
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.563404869
Minimum1
Maximum10
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:56:38.747855image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q15
median9
Q310
95-th percentile10
Maximum10
Range9
Interquartile range (IQR)5

Descriptive statistics

Standard deviation3.024221891
Coefficient of variation (CV)0.3998492667
Kurtosis-0.564029077
Mean7.563404869
Median Absolute Deviation (MAD)1
Skewness-0.9277928841
Sum324939
Variance9.145918045
MonotocityNot monotonic
2020-11-30T23:56:38.829815image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
101987146.3%
 
9503811.7%
 
541109.6%
 
126746.2%
 
822495.2%
 
220544.8%
 
620064.7%
 
418394.3%
 
717024.0%
 
314193.3%
 
ValueCountFrequency (%) 
126746.2%
 
220544.8%
 
314193.3%
 
418394.3%
 
541109.6%
 
620064.7%
 
717024.0%
 
822495.2%
 
9503811.7%
 
101987146.3%
 
ValueCountFrequency (%) 
101987146.3%
 
9503811.7%
 
822495.2%
 
717024.0%
 
620064.7%
 
541109.6%
 
418394.3%
 
314193.3%
 
220544.8%
 
126746.2%
 

D19_GESAMT_ONLINE_QUOTE_12
Real number (ℝ≥0)

MISSING
ZEROS

Distinct11
Distinct (%)< 0.1%
Missing7584
Missing (%)17.7%
Infinite0
Infinite (%)0.0%
Mean2.90202951
Minimum0
Maximum10
Zeros23291
Zeros (%)54.2%
Memory size335.8 KiB
2020-11-30T23:56:38.920455image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q38
95-th percentile10
Maximum10
Range10
Interquartile range (IQR)8

Descriptive statistics

Standard deviation4.297059574
Coefficient of variation (CV)1.480708435
Kurtosis-1.053842881
Mean2.90202951
Median Absolute Deviation (MAD)0
Skewness0.9127195684
Sum102668
Variance18.46472098
MonotocityNot monotonic
2020-11-30T23:56:39.004054image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%) 
02329154.2%
 
10817119.0%
 
510092.3%
 
86291.5%
 
75311.2%
 
35201.2%
 
93370.8%
 
12830.7%
 
22500.6%
 
61800.4%
 
41770.4%
 
(Missing)758417.7%
 
ValueCountFrequency (%) 
02329154.2%
 
12830.7%
 
22500.6%
 
35201.2%
 
41770.4%
 
510092.3%
 
61800.4%
 
75311.2%
 
86291.5%
 
93370.8%
 
ValueCountFrequency (%) 
10817119.0%
 
93370.8%
 
86291.5%
 
75311.2%
 
61800.4%
 
510092.3%
 
41770.4%
 
35201.2%
 
22500.6%
 
12830.7%
 

D19_HANDWERK
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.687374889
Minimum0
Maximum7
Zeros31086
Zeros (%)72.4%
Memory size335.8 KiB
2020-11-30T23:56:39.084360image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q36
95-th percentile6
Maximum7
Range7
Interquartile range (IQR)6

Descriptive statistics

Standard deviation2.746567981
Coefficient of variation (CV)1.627716519
Kurtosis-0.8870511223
Mean1.687374889
Median Absolute Deviation (MAD)0
Skewness1.034615326
Sum72493
Variance7.543635673
MonotocityNot monotonic
2020-11-30T23:56:39.164518image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
03108672.4%
 
6937821.8%
 
720574.8%
 
52500.6%
 
31800.4%
 
48< 0.1%
 
12< 0.1%
 
21< 0.1%
 
ValueCountFrequency (%) 
03108672.4%
 
12< 0.1%
 
21< 0.1%
 
31800.4%
 
48< 0.1%
 
52500.6%
 
6937821.8%
 
720574.8%
 
ValueCountFrequency (%) 
720574.8%
 
6937821.8%
 
52500.6%
 
48< 0.1%
 
31800.4%
 
21< 0.1%
 
12< 0.1%
 
03108672.4%
 

D19_HAUS_DEKO
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.624249337
Minimum0
Maximum7
Zeros28556
Zeros (%)66.5%
Memory size335.8 KiB
2020-11-30T23:56:39.252121image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q33
95-th percentile6
Maximum7
Range7
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.475151796
Coefficient of variation (CV)1.523874285
Kurtosis-0.7451399847
Mean1.624249337
Median Absolute Deviation (MAD)0
Skewness1.030271963
Sum69781
Variance6.126376412
MonotocityNot monotonic
2020-11-30T23:56:39.331412image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
02855666.5%
 
6800418.6%
 
327146.3%
 
515263.6%
 
27901.8%
 
17011.6%
 
73400.8%
 
43310.8%
 
ValueCountFrequency (%) 
02855666.5%
 
17011.6%
 
27901.8%
 
327146.3%
 
43310.8%
 
515263.6%
 
6800418.6%
 
73400.8%
 
ValueCountFrequency (%) 
73400.8%
 
6800418.6%
 
515263.6%
 
43310.8%
 
327146.3%
 
27901.8%
 
17011.6%
 
02855666.5%
 

D19_KINDERARTIKEL
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.168427913
Minimum0
Maximum7
Zeros33786
Zeros (%)78.6%
Memory size335.8 KiB
2020-11-30T23:56:39.416986image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile6
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.341262999
Coefficient of variation (CV)2.003771883
Kurtosis0.7894047878
Mean1.168427913
Median Absolute Deviation (MAD)0
Skewness1.617544674
Sum50198
Variance5.481512433
MonotocityNot monotonic
2020-11-30T23:56:39.498896image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
03378678.6%
 
6505611.8%
 
716473.8%
 
311802.7%
 
56691.6%
 
23320.8%
 
41640.4%
 
11280.3%
 
ValueCountFrequency (%) 
03378678.6%
 
11280.3%
 
23320.8%
 
311802.7%
 
41640.4%
 
56691.6%
 
6505611.8%
 
716473.8%
 
ValueCountFrequency (%) 
716473.8%
 
6505611.8%
 
56691.6%
 
41640.4%
 
311802.7%
 
23320.8%
 
11280.3%
 
03378678.6%
 

D19_KONSUMTYP
Real number (ℝ≥0)

MISSING

Distinct7
Distinct (%)< 0.1%
Missing7584
Missing (%)17.7%
Infinite0
Infinite (%)0.0%
Mean3.695884448
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:56:39.589102image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile9
Maximum9
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.761664716
Coefficient of variation (CV)0.7472270184
Kurtosis-0.2748055142
Mean3.695884448
Median Absolute Deviation (MAD)1
Skewness1.069897628
Sum130753
Variance7.626792005
MonotocityNot monotonic
2020-11-30T23:56:39.672428image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
31144226.6%
 
1775018.0%
 
9644315.0%
 
2598713.9%
 
416533.8%
 
615893.7%
 
55141.2%
 
(Missing)758417.7%
 
ValueCountFrequency (%) 
1775018.0%
 
2598713.9%
 
31144226.6%
 
416533.8%
 
55141.2%
 
615893.7%
 
9644315.0%
 
ValueCountFrequency (%) 
9644315.0%
 
615893.7%
 
55141.2%
 
416533.8%
 
31144226.6%
 
2598713.9%
 
1775018.0%
 

D19_KONSUMTYP_MAX
Real number (ℝ≥0)

Distinct6
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.612518039
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:56:39.762051image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q38
95-th percentile9
Maximum9
Range8
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.219637653
Coefficient of variation (CV)0.6980216934
Kurtosis-1.732328883
Mean4.612518039
Median Absolute Deviation (MAD)2
Skewness0.3138652574
Sum198163
Variance10.36606661
MonotocityNot monotonic
2020-11-30T23:56:39.845586image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
21429733.3%
 
8967322.5%
 
9758417.7%
 
1636614.8%
 
326056.1%
 
424375.7%
 
ValueCountFrequency (%) 
1636614.8%
 
21429733.3%
 
326056.1%
 
424375.7%
 
8967322.5%
 
9758417.7%
 
ValueCountFrequency (%) 
9758417.7%
 
8967322.5%
 
424375.7%
 
326056.1%
 
21429733.3%
 
1636614.8%
 

D19_KOSMETIK
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.108188632
Minimum0
Maximum7
Zeros28919
Zeros (%)67.3%
Memory size335.8 KiB
2020-11-30T23:56:39.939405image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q36
95-th percentile7
Maximum7
Range7
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.043675997
Coefficient of variation (CV)1.443739878
Kurtosis-1.359773033
Mean2.108188632
Median Absolute Deviation (MAD)0
Skewness0.7729636282
Sum90572
Variance9.263963577
MonotocityNot monotonic
2020-11-30T23:56:40.020566image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
02891967.3%
 
6722916.8%
 
7665915.5%
 
3740.2%
 
5630.1%
 
48< 0.1%
 
26< 0.1%
 
14< 0.1%
 
ValueCountFrequency (%) 
02891967.3%
 
14< 0.1%
 
26< 0.1%
 
3740.2%
 
48< 0.1%
 
5630.1%
 
6722916.8%
 
7665915.5%
 
ValueCountFrequency (%) 
7665915.5%
 
6722916.8%
 
5630.1%
 
48< 0.1%
 
3740.2%
 
26< 0.1%
 
14< 0.1%
 
02891967.3%
 

D19_LEBENSMITTEL
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.6862343466
Minimum0
Maximum7
Zeros37467
Zeros (%)87.2%
Memory size335.8 KiB
2020-11-30T23:56:40.106948image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile6
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.853459469
Coefficient of variation (CV)2.700913293
Kurtosis4.266564666
Mean0.6862343466
Median Absolute Deviation (MAD)0
Skewness2.453815764
Sum29482
Variance3.435312004
MonotocityNot monotonic
2020-11-30T23:56:40.189758image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
03746787.2%
 
632437.5%
 
39572.2%
 
56231.5%
 
75301.2%
 
2810.2%
 
4350.1%
 
1260.1%
 
ValueCountFrequency (%) 
03746787.2%
 
1260.1%
 
2810.2%
 
39572.2%
 
4350.1%
 
56231.5%
 
632437.5%
 
75301.2%
 
ValueCountFrequency (%) 
75301.2%
 
632437.5%
 
56231.5%
 
4350.1%
 
39572.2%
 
2810.2%
 
1260.1%
 
03746787.2%
 

D19_LETZTER_KAUF_BRANCHE
Categorical

MISSING

Distinct35
Distinct (%)0.1%
Missing7584
Missing (%)17.7%
Memory size335.8 KiB
D19_UNBEKANNT
10276 
D19_SONSTIGE
2753 
D19_VERSICHERUNGEN
2662 
D19_VOLLSORTIMENT
2289 
D19_HAUS_DEKO
2224 
Other values (30)
15174 
ValueCountFrequency (%) 
D19_UNBEKANNT1027623.9%
 
D19_SONSTIGE27536.4%
 
D19_VERSICHERUNGEN26626.2%
 
D19_VOLLSORTIMENT22895.3%
 
D19_HAUS_DEKO22245.2%
 
D19_BUCH_CD20894.9%
 
D19_DROGERIEARTIKEL11122.6%
 
D19_BEKLEIDUNG_REST10562.5%
 
D19_BEKLEIDUNG_GEH10542.5%
 
D19_SCHUHE10422.4%
 
D19_ENERGIE10072.3%
 
D19_VERSAND_REST8121.9%
 
D19_LEBENSMITTEL7821.8%
 
D19_BANKEN_DIREKT7311.7%
 
D19_NAHRUNGSERGAENZUNG5561.3%
 
D19_TELKO_MOBILE5441.3%
 
D19_TELKO_REST5391.3%
 
D19_BANKEN_GROSS4261.0%
 
D19_SAMMELARTIKEL4141.0%
 
D19_FREIZEIT3980.9%
 
D19_TECHNIK3820.9%
 
D19_WEIN_FEINKOST3110.7%
 
D19_KINDERARTIKEL3040.7%
 
D19_RATGEBER3020.7%
 
D19_DIGIT_SERV2170.5%
 
Other values (10)10962.6%
 
(Missing)758417.7%
 
2020-11-30T23:56:40.307285image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters26
Unique unicode categories4 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
E5391310.2%
 
N5277010.0%
 
_458318.7%
 
D451488.5%
 
1353786.7%
 
9353786.7%
 
T275305.2%
 
U215754.1%
 
K211884.0%
 
R205413.9%
 
S204403.9%
 
I189853.6%
 
A188563.6%
 
B177703.4%
 
n151682.9%
 
O137182.6%
 
G135382.6%
 
L124602.4%
 
H111622.1%
 
C82641.6%
 
a75841.4%
 
V59801.1%
 
M44630.8%
 
Z9540.2%
 
F7090.1%
 

Most occurring categories

ValueCountFrequency (%) 
Uppercase Letter39038673.7%
 
Decimal Number7075613.4%
 
Connector Punctuation458318.7%
 
Lowercase Letter227524.3%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
E5391313.8%
 
N5277013.5%
 
D4514811.6%
 
T275307.1%
 
U215755.5%
 
K211885.4%
 
R205415.3%
 
S204405.2%
 
I189854.9%
 
A188564.8%
 
B177704.6%
 
O137183.5%
 
G135383.5%
 
L124603.2%
 
H111622.9%
 
C82642.1%
 
V59801.5%
 
M44631.1%
 
Z9540.2%
 
F7090.2%
 
W4220.1%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
13537850.0%
 
93537850.0%
 

Most frequent Connector Punctuation characters

ValueCountFrequency (%) 
_45831100.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n1516866.7%
 
a758433.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin41313878.0%
 
Common11658722.0%
 

Most frequent Latin characters

ValueCountFrequency (%) 
E5391313.0%
 
N5277012.8%
 
D4514810.9%
 
T275306.7%
 
U215755.2%
 
K211885.1%
 
R205415.0%
 
S204404.9%
 
I189854.6%
 
A188564.6%
 
B177704.3%
 
n151683.7%
 
O137183.3%
 
G135383.3%
 
L124603.0%
 
H111622.7%
 
C82642.0%
 
a75841.8%
 
V59801.4%
 
M44631.1%
 
Z9540.2%
 
F7090.2%
 
W4220.1%
 

Most frequent Common characters

ValueCountFrequency (%) 
_4583139.3%
 
13537830.3%
 
93537830.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII529725100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
E5391310.2%
 
N5277010.0%
 
_458318.7%
 
D451488.5%
 
1353786.7%
 
9353786.7%
 
T275305.2%
 
U215754.1%
 
K211884.0%
 
R205413.9%
 
S204403.9%
 
I189853.6%
 
A188563.6%
 
B177703.4%
 
n151682.9%
 
O137182.6%
 
G135382.6%
 
L124602.4%
 
H111622.1%
 
C82641.6%
 
a75841.4%
 
V59801.1%
 
M44630.8%
 
Z9540.2%
 
F7090.1%
 

D19_LOTTO
Real number (ℝ≥0)

MISSING
ZEROS

Distinct7
Distinct (%)< 0.1%
Missing7584
Missing (%)17.7%
Infinite0
Infinite (%)0.0%
Mean2.905930239
Minimum0
Maximum7
Zeros20293
Zeros (%)47.2%
Memory size335.8 KiB
2020-11-30T23:56:40.402035image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q37
95-th percentile7
Maximum7
Range7
Interquartile range (IQR)7

Descriptive statistics

Standard deviation3.386266181
Coefficient of variation (CV)1.16529507
Kurtosis-1.877900534
Mean2.905930239
Median Absolute Deviation (MAD)0
Skewness0.320095582
Sum102806
Variance11.46679865
MonotocityNot monotonic
2020-11-30T23:56:40.484689image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
02029347.2%
 
71271429.6%
 
621745.1%
 
31080.3%
 
5860.2%
 
42< 0.1%
 
21< 0.1%
 
(Missing)758417.7%
 
ValueCountFrequency (%) 
02029347.2%
 
21< 0.1%
 
31080.3%
 
42< 0.1%
 
5860.2%
 
621745.1%
 
71271429.6%
 
ValueCountFrequency (%) 
71271429.6%
 
621745.1%
 
5860.2%
 
42< 0.1%
 
31080.3%
 
21< 0.1%
 
02029347.2%
 

D19_NAHRUNGSERGAENZUNG
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.563497975
Minimum0
Maximum7
Zeros38508
Zeros (%)89.6%
Memory size335.8 KiB
2020-11-30T23:56:40.573094image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile6
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.713365835
Coefficient of variation (CV)3.040589161
Kurtosis6.360326696
Mean0.563497975
Median Absolute Deviation (MAD)0
Skewness2.841325911
Sum24209
Variance2.935622484
MonotocityNot monotonic
2020-11-30T23:56:40.656656image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
03850889.6%
 
624685.7%
 
36951.6%
 
76231.5%
 
55341.2%
 
2550.1%
 
1470.1%
 
4320.1%
 
ValueCountFrequency (%) 
03850889.6%
 
1470.1%
 
2550.1%
 
36951.6%
 
4320.1%
 
55341.2%
 
624685.7%
 
76231.5%
 
ValueCountFrequency (%) 
76231.5%
 
624685.7%
 
55341.2%
 
4320.1%
 
36951.6%
 
2550.1%
 
1470.1%
 
03850889.6%
 

D19_RATGEBER
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.9156463852
Minimum0
Maximum7
Zeros35306
Zeros (%)82.2%
Memory size335.8 KiB
2020-11-30T23:56:40.746349image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile6
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.072453944
Coefficient of variation (CV)2.263378066
Kurtosis2.075685705
Mean0.9156463852
Median Absolute Deviation (MAD)0
Skewness1.964237218
Sum39338
Variance4.29506535
MonotocityNot monotonic
2020-11-30T23:56:40.828302image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
03530682.2%
 
6459110.7%
 
310512.4%
 
26321.5%
 
55661.3%
 
75371.2%
 
41690.4%
 
11100.3%
 
ValueCountFrequency (%) 
03530682.2%
 
11100.3%
 
26321.5%
 
310512.4%
 
41690.4%
 
55661.3%
 
6459110.7%
 
75371.2%
 
ValueCountFrequency (%) 
75371.2%
 
6459110.7%
 
55661.3%
 
41690.4%
 
310512.4%
 
26321.5%
 
11100.3%
 
03530682.2%
 

D19_REISEN
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.060588427
Minimum0
Maximum7
Zeros28298
Zeros (%)65.9%
Memory size335.8 KiB
2020-11-30T23:56:40.919349image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q36
95-th percentile7
Maximum7
Range7
Interquartile range (IQR)6

Descriptive statistics

Standard deviation2.920401013
Coefficient of variation (CV)1.417265561
Kurtosis-1.357436218
Mean2.060588427
Median Absolute Deviation (MAD)0
Skewness0.7582206081
Sum88527
Variance8.528742076
MonotocityNot monotonic
2020-11-30T23:56:40.999261image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
02829865.9%
 
6961022.4%
 
738338.9%
 
34721.1%
 
53410.8%
 
23360.8%
 
4570.1%
 
115< 0.1%
 
ValueCountFrequency (%) 
02829865.9%
 
115< 0.1%
 
23360.8%
 
34721.1%
 
4570.1%
 
53410.8%
 
6961022.4%
 
738338.9%
 
ValueCountFrequency (%) 
738338.9%
 
6961022.4%
 
53410.8%
 
4570.1%
 
34721.1%
 
23360.8%
 
115< 0.1%
 
02829865.9%
 

D19_SAMMELARTIKEL
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.491899818
Minimum0
Maximum7
Zeros31986
Zeros (%)74.5%
Memory size335.8 KiB
2020-11-30T23:56:41.083861image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q33
95-th percentile6
Maximum7
Range7
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.579540198
Coefficient of variation (CV)1.729030439
Kurtosis-0.5389752606
Mean1.491899818
Median Absolute Deviation (MAD)0
Skewness1.185656488
Sum64095
Variance6.654027633
MonotocityNot monotonic
2020-11-30T23:56:41.164139image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
03198674.5%
 
6890420.7%
 
78141.9%
 
55931.4%
 
35321.2%
 
4790.2%
 
2420.1%
 
112< 0.1%
 
ValueCountFrequency (%) 
03198674.5%
 
112< 0.1%
 
2420.1%
 
35321.2%
 
4790.2%
 
55931.4%
 
6890420.7%
 
78141.9%
 
ValueCountFrequency (%) 
78141.9%
 
6890420.7%
 
55931.4%
 
4790.2%
 
35321.2%
 
2420.1%
 
112< 0.1%
 
03198674.5%
 

D19_SCHUHE
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.5499278432
Minimum0
Maximum7
Zeros37508
Zeros (%)87.3%
Memory size335.8 KiB
2020-11-30T23:56:41.251617image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile5
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.558936622
Coefficient of variation (CV)2.834802131
Kurtosis6.477371411
Mean0.5499278432
Median Absolute Deviation (MAD)0
Skewness2.79274952
Sum23626
Variance2.430283391
MonotocityNot monotonic
2020-11-30T23:56:41.333935image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
03750887.3%
 
618274.3%
 
317154.0%
 
58632.0%
 
25291.2%
 
72140.5%
 
11920.4%
 
41140.3%
 
ValueCountFrequency (%) 
03750887.3%
 
11920.4%
 
25291.2%
 
317154.0%
 
41140.3%
 
58632.0%
 
618274.3%
 
72140.5%
 
ValueCountFrequency (%) 
72140.5%
 
618274.3%
 
58632.0%
 
41140.3%
 
317154.0%
 
25291.2%
 
11920.4%
 
03750887.3%
 

D19_SONSTIGE
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.617941437
Minimum0
Maximum7
Zeros15258
Zeros (%)35.5%
Memory size335.8 KiB
2020-11-30T23:56:41.421786image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median5
Q36
95-th percentile7
Maximum7
Range7
Interquartile range (IQR)6

Descriptive statistics

Standard deviation2.892432674
Coefficient of variation (CV)0.7994691801
Kurtosis-1.723978843
Mean3.617941437
Median Absolute Deviation (MAD)2
Skewness-0.2962165328
Sum155434
Variance8.366166773
MonotocityNot monotonic
2020-11-30T23:56:41.505594image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
61618337.7%
 
01525835.5%
 
7516212.0%
 
328916.7%
 
519694.6%
 
27121.7%
 
44911.1%
 
12960.7%
 
ValueCountFrequency (%) 
01525835.5%
 
12960.7%
 
27121.7%
 
328916.7%
 
44911.1%
 
519694.6%
 
61618337.7%
 
7516212.0%
 
ValueCountFrequency (%) 
7516212.0%
 
61618337.7%
 
519694.6%
 
44911.1%
 
328916.7%
 
27121.7%
 
12960.7%
 
01525835.5%
 

D19_SOZIALES
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing7584
Missing (%)17.7%
Infinite0
Infinite (%)0.0%
Mean1.69410368
Minimum0
Maximum5
Zeros9615
Zeros (%)22.4%
Memory size335.8 KiB
2020-11-30T23:56:41.593187image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q33
95-th percentile4
Maximum5
Range5
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.510322811
Coefficient of variation (CV)0.8915173425
Kurtosis-0.9806251656
Mean1.69410368
Median Absolute Deviation (MAD)1
Skewness0.4988485443
Sum59934
Variance2.281074993
MonotocityNot monotonic
2020-11-30T23:56:41.675872image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
11099125.6%
 
0961522.4%
 
3862420.1%
 
431967.4%
 
214913.5%
 
514613.4%
 
(Missing)758417.7%
 
ValueCountFrequency (%) 
0961522.4%
 
11099125.6%
 
214913.5%
 
3862420.1%
 
431967.4%
 
514613.4%
 
ValueCountFrequency (%) 
514613.4%
 
431967.4%
 
3862420.1%
 
214913.5%
 
11099125.6%
 
0961522.4%
 

D19_TECHNIK
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.460104278
Minimum0
Maximum7
Zeros25369
Zeros (%)59.0%
Memory size335.8 KiB
2020-11-30T23:56:41.757359image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q36
95-th percentile7
Maximum7
Range7
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.013667797
Coefficient of variation (CV)1.225016282
Kurtosis-1.710391779
Mean2.460104278
Median Absolute Deviation (MAD)0
Skewness0.4604807392
Sum105691
Variance9.082193588
MonotocityNot monotonic
2020-11-30T23:56:41.836094image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
02536959.0%
 
61129226.3%
 
7430610.0%
 
59122.1%
 
39122.1%
 
4860.2%
 
2720.2%
 
113< 0.1%
 
ValueCountFrequency (%) 
02536959.0%
 
113< 0.1%
 
2720.2%
 
39122.1%
 
4860.2%
 
59122.1%
 
61129226.3%
 
7430610.0%
 
ValueCountFrequency (%) 
7430610.0%
 
61129226.3%
 
59122.1%
 
4860.2%
 
39122.1%
 
2720.2%
 
113< 0.1%
 
02536959.0%
 

D19_TELKO_ANZ_12
Real number (ℝ≥0)

ZEROS

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.05355895908
Minimum0
Maximum6
Zeros41099
Zeros (%)95.7%
Memory size335.8 KiB
2020-11-30T23:56:41.921969image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum6
Range6
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.2730818605
Coefficient of variation (CV)5.09871486
Kurtosis49.50906931
Mean0.05355895908
Median Absolute Deviation (MAD)0
Skewness6.231514103
Sum2301
Variance0.07457370255
MonotocityNot monotonic
2020-11-30T23:56:42.003503image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
04109995.7%
 
114813.4%
 
23410.8%
 
3290.1%
 
410< 0.1%
 
61< 0.1%
 
51< 0.1%
 
ValueCountFrequency (%) 
04109995.7%
 
114813.4%
 
23410.8%
 
3290.1%
 
410< 0.1%
 
51< 0.1%
 
61< 0.1%
 
ValueCountFrequency (%) 
61< 0.1%
 
51< 0.1%
 
410< 0.1%
 
3290.1%
 
23410.8%
 
114813.4%
 
04109995.7%
 

D19_TELKO_ANZ_24
Real number (ℝ≥0)

ZEROS

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.09627112332
Minimum0
Maximum6
Zeros39720
Zeros (%)92.5%
Memory size335.8 KiB
2020-11-30T23:56:42.089324image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum6
Range6
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.3688173323
Coefficient of variation (CV)3.831027618
Kurtosis26.3568111
Mean0.09627112332
Median Absolute Deviation (MAD)0
Skewness4.617613337
Sum4136
Variance0.1360262246
MonotocityNot monotonic
2020-11-30T23:56:42.170379image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
03972092.5%
 
124695.7%
 
26841.6%
 
3620.1%
 
4230.1%
 
53< 0.1%
 
61< 0.1%
 
ValueCountFrequency (%) 
03972092.5%
 
124695.7%
 
26841.6%
 
3620.1%
 
4230.1%
 
53< 0.1%
 
61< 0.1%
 
ValueCountFrequency (%) 
61< 0.1%
 
53< 0.1%
 
4230.1%
 
3620.1%
 
26841.6%
 
124695.7%
 
03972092.5%
 

D19_TELKO_DATUM
Real number (ℝ≥0)

Distinct10
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.465620781
Minimum1
Maximum10
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:56:42.269587image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6
Q110
median10
Q310
95-th percentile10
Maximum10
Range9
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.33337358
Coefficient of variation (CV)0.1408648847
Kurtosis10.59028856
Mean9.465620781
Median Absolute Deviation (MAD)0
Skewness-3.157357748
Sum406662
Variance1.777885103
MonotocityNot monotonic
2020-11-30T23:56:42.359887image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
103357178.1%
 
9456310.6%
 
815863.7%
 
513513.1%
 
77061.6%
 
66731.6%
 
42240.5%
 
21000.2%
 
1990.2%
 
3890.2%
 
ValueCountFrequency (%) 
1990.2%
 
21000.2%
 
3890.2%
 
42240.5%
 
513513.1%
 
66731.6%
 
77061.6%
 
815863.7%
 
9456310.6%
 
103357178.1%
 
ValueCountFrequency (%) 
103357178.1%
 
9456310.6%
 
815863.7%
 
77061.6%
 
66731.6%
 
513513.1%
 
42240.5%
 
3890.2%
 
21000.2%
 
1990.2%
 

D19_TELKO_MOBILE
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.8581769936
Minimum0
Maximum7
Zeros36119
Zeros (%)84.1%
Memory size335.8 KiB
2020-11-30T23:56:42.455746image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile6
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.034735216
Coefficient of variation (CV)2.370997162
Kurtosis2.355745115
Mean0.8581769936
Median Absolute Deviation (MAD)0
Skewness2.046708537
Sum36869
Variance4.140147399
MonotocityNot monotonic
2020-11-30T23:56:42.548575image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
03611984.1%
 
6462310.8%
 
39932.3%
 
56001.4%
 
73390.8%
 
41280.3%
 
21070.2%
 
1530.1%
 
ValueCountFrequency (%) 
03611984.1%
 
1530.1%
 
21070.2%
 
39932.3%
 
41280.3%
 
56001.4%
 
6462310.8%
 
73390.8%
 
ValueCountFrequency (%) 
73390.8%
 
6462310.8%
 
56001.4%
 
41280.3%
 
39932.3%
 
21070.2%
 
1530.1%
 
03611984.1%
 

D19_TELKO_OFFLINE_DATUM
Real number (ℝ≥0)

Distinct10
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.776127741
Minimum1
Maximum10
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:56:42.639932image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile9
Q110
median10
Q310
95-th percentile10
Maximum10
Range9
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.9077051287
Coefficient of variation (CV)0.09284914771
Kurtosis27.54580377
Mean9.776127741
Median Absolute Deviation (MAD)0
Skewness-5.02947815
Sum420002
Variance0.8239286006
MonotocityNot monotonic
2020-11-30T23:56:42.722245image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
103918391.2%
 
917344.0%
 
58281.9%
 
87071.6%
 
62300.5%
 
71490.3%
 
4480.1%
 
2320.1%
 
1310.1%
 
320< 0.1%
 
ValueCountFrequency (%) 
1310.1%
 
2320.1%
 
320< 0.1%
 
4480.1%
 
58281.9%
 
62300.5%
 
71490.3%
 
87071.6%
 
917344.0%
 
103918391.2%
 
ValueCountFrequency (%) 
103918391.2%
 
917344.0%
 
87071.6%
 
71490.3%
 
62300.5%
 
58281.9%
 
4480.1%
 
320< 0.1%
 
2320.1%
 
1310.1%
 

D19_TELKO_ONLINE_DATUM
Real number (ℝ≥0)

Distinct10
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.978841767
Minimum1
Maximum10
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:56:42.809696image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile10
Q110
median10
Q310
95-th percentile10
Maximum10
Range9
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.2514253572
Coefficient of variation (CV)0.02519584568
Kurtosis370.0917397
Mean9.978841767
Median Absolute Deviation (MAD)0
Skewness-17.124395
Sum428711
Variance0.06321471023
MonotocityNot monotonic
2020-11-30T23:56:42.891407image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
104249398.9%
 
92600.6%
 
81060.2%
 
7400.1%
 
5300.1%
 
6230.1%
 
33< 0.1%
 
23< 0.1%
 
42< 0.1%
 
12< 0.1%
 
ValueCountFrequency (%) 
12< 0.1%
 
23< 0.1%
 
33< 0.1%
 
42< 0.1%
 
5300.1%
 
6230.1%
 
7400.1%
 
81060.2%
 
92600.6%
 
104249398.9%
 
ValueCountFrequency (%) 
104249398.9%
 
92600.6%
 
81060.2%
 
7400.1%
 
6230.1%
 
5300.1%
 
42< 0.1%
 
33< 0.1%
 
23< 0.1%
 
12< 0.1%
 

D19_TELKO_ONLINE_QUOTE_12
Categorical

MISSING

Distinct3
Distinct (%)< 0.1%
Missing7584
Missing (%)17.7%
Memory size335.8 KiB
0
35338 
10
 
37
5
 
3
ValueCountFrequency (%) 
03533882.3%
 
10370.1%
 
53< 0.1%
 
(Missing)758417.7%
 
2020-11-30T23:56:42.996997image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters6
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
07075354.9%
 
.3537827.4%
 
n1516811.8%
 
a75845.9%
 
137< 0.1%
 
53< 0.1%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number7079354.9%
 
Other Punctuation3537827.4%
 
Lowercase Letter2275217.6%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
07075399.9%
 
1370.1%
 
53< 0.1%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
.35378100.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n1516866.7%
 
a758433.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Common10617182.4%
 
Latin2275217.6%
 

Most frequent Common characters

ValueCountFrequency (%) 
07075366.6%
 
.3537833.3%
 
137< 0.1%
 
53< 0.1%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n1516866.7%
 
a758433.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII128923100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
07075354.9%
 
.3537827.4%
 
n1516811.8%
 
a75845.9%
 
137< 0.1%
 
53< 0.1%
 

D19_TELKO_REST
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.6160327731
Minimum0
Maximum7
Zeros37986
Zeros (%)88.4%
Memory size335.8 KiB
2020-11-30T23:56:43.085538image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile6
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.753162898
Coefficient of variation (CV)2.845892254
Kurtosis5.047523719
Mean0.6160327731
Median Absolute Deviation (MAD)0
Skewness2.609397689
Sum26466
Variance3.073580145
MonotocityNot monotonic
2020-11-30T23:56:43.166167image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
03798688.4%
 
630617.1%
 
38041.9%
 
57231.7%
 
72320.5%
 
2740.2%
 
4730.2%
 
19< 0.1%
 
ValueCountFrequency (%) 
03798688.4%
 
19< 0.1%
 
2740.2%
 
38041.9%
 
4730.2%
 
57231.7%
 
630617.1%
 
72320.5%
 
ValueCountFrequency (%) 
72320.5%
 
630617.1%
 
57231.7%
 
4730.2%
 
38041.9%
 
2740.2%
 
19< 0.1%
 
03798688.4%
 

D19_TIERARTIKEL
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.2645826544
Minimum0
Maximum7
Zeros40917
Zeros (%)95.2%
Memory size335.8 KiB
2020-11-30T23:56:43.254883image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.223280465
Coefficient of variation (CV)4.623434094
Kurtosis19.83859882
Mean0.2645826544
Median Absolute Deviation (MAD)0
Skewness4.604508592
Sum11367
Variance1.496415097
MonotocityNot monotonic
2020-11-30T23:56:43.338453image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
04091795.2%
 
69072.1%
 
75291.2%
 
33500.8%
 
52030.5%
 
2320.1%
 
4230.1%
 
11< 0.1%
 
ValueCountFrequency (%) 
04091795.2%
 
11< 0.1%
 
2320.1%
 
33500.8%
 
4230.1%
 
52030.5%
 
69072.1%
 
75291.2%
 
ValueCountFrequency (%) 
75291.2%
 
69072.1%
 
52030.5%
 
4230.1%
 
33500.8%
 
2320.1%
 
11< 0.1%
 
04091795.2%
 

D19_VERSAND_ANZ_12
Real number (ℝ≥0)

ZEROS

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.7746613286
Minimum0
Maximum6
Zeros27763
Zeros (%)64.6%
Memory size335.8 KiB
2020-11-30T23:56:43.427624image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile4
Maximum6
Range6
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.288737161
Coefficient of variation (CV)1.663613651
Kurtosis2.380534371
Mean0.7746613286
Median Absolute Deviation (MAD)0
Skewness1.7558783
Sum33281
Variance1.66084347
MonotocityNot monotonic
2020-11-30T23:56:43.503706image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
02776364.6%
 
1582613.6%
 
2454510.6%
 
320334.7%
 
418774.4%
 
57501.7%
 
61680.4%
 
ValueCountFrequency (%) 
02776364.6%
 
1582613.6%
 
2454510.6%
 
320334.7%
 
418774.4%
 
57501.7%
 
61680.4%
 
ValueCountFrequency (%) 
61680.4%
 
57501.7%
 
418774.4%
 
320334.7%
 
2454510.6%
 
1582613.6%
 
02776364.6%
 

D19_VERSAND_ANZ_24
Real number (ℝ≥0)

ZEROS

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.193473302
Minimum0
Maximum6
Zeros23413
Zeros (%)54.5%
Memory size335.8 KiB
2020-11-30T23:56:43.585943image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile5
Maximum6
Range6
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.64398307
Coefficient of variation (CV)1.377477877
Kurtosis0.495740851
Mean1.193473302
Median Absolute Deviation (MAD)0
Skewness1.260563113
Sum51274
Variance2.702680336
MonotocityNot monotonic
2020-11-30T23:56:43.661373image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
02341354.5%
 
2556713.0%
 
1553312.9%
 
430427.1%
 
327026.3%
 
518974.4%
 
68081.9%
 
ValueCountFrequency (%) 
02341354.5%
 
1553312.9%
 
2556713.0%
 
327026.3%
 
430427.1%
 
518974.4%
 
68081.9%
 
ValueCountFrequency (%) 
68081.9%
 
518974.4%
 
430427.1%
 
327026.3%
 
2556713.0%
 
1553312.9%
 
02341354.5%
 

D19_VERSAND_DATUM
Real number (ℝ≥0)

Distinct10
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.168590848
Minimum1
Maximum10
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:56:43.746647image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q15
median9
Q310
95-th percentile10
Maximum10
Range9
Interquartile range (IQR)5

Descriptive statistics

Standard deviation3.027906857
Coefficient of variation (CV)0.4223852248
Kurtosis-0.8576203016
Mean7.168590848
Median Absolute Deviation (MAD)1
Skewness-0.7258834537
Sum307977
Variance9.168219932
MonotocityNot monotonic
2020-11-30T23:56:43.828559image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
101483634.5%
 
9694816.2%
 
5505511.8%
 
830647.1%
 
128516.6%
 
224855.8%
 
622405.2%
 
419604.6%
 
719074.4%
 
316163.8%
 
ValueCountFrequency (%) 
128516.6%
 
224855.8%
 
316163.8%
 
419604.6%
 
5505511.8%
 
622405.2%
 
719074.4%
 
830647.1%
 
9694816.2%
 
101483634.5%
 
ValueCountFrequency (%) 
101483634.5%
 
9694816.2%
 
830647.1%
 
719074.4%
 
622405.2%
 
5505511.8%
 
419604.6%
 
316163.8%
 
224855.8%
 
128516.6%
 

D19_VERSAND_OFFLINE_DATUM
Real number (ℝ≥0)

Distinct10
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.471812299
Minimum1
Maximum10
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:56:46.466535image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4
Q18
median9
Q310
95-th percentile10
Maximum10
Range9
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.149832953
Coefficient of variation (CV)0.2537630529
Kurtosis1.9222907
Mean8.471812299
Median Absolute Deviation (MAD)1
Skewness-1.622498229
Sum363966
Variance4.621781725
MonotocityNot monotonic
2020-11-30T23:56:46.561384image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
101993946.4%
 
9966022.5%
 
839959.3%
 
534238.0%
 
717944.2%
 
615733.7%
 
28151.9%
 
47161.7%
 
15351.2%
 
35121.2%
 
ValueCountFrequency (%) 
15351.2%
 
28151.9%
 
35121.2%
 
47161.7%
 
534238.0%
 
615733.7%
 
717944.2%
 
839959.3%
 
9966022.5%
 
101993946.4%
 
ValueCountFrequency (%) 
101993946.4%
 
9966022.5%
 
839959.3%
 
717944.2%
 
615733.7%
 
534238.0%
 
47161.7%
 
35121.2%
 
28151.9%
 
15351.2%
 

D19_VERSAND_ONLINE_DATUM
Real number (ℝ≥0)

Distinct10
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.82775476
Minimum1
Maximum10
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:56:46.657696image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q16
median10
Q310
95-th percentile10
Maximum10
Range9
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.937353179
Coefficient of variation (CV)0.3752484932
Kurtosis-0.1892625845
Mean7.82775476
Median Absolute Deviation (MAD)0
Skewness-1.105158743
Sum336296
Variance8.628043696
MonotocityNot monotonic
2020-11-30T23:56:46.769264image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
102184550.8%
 
9504511.7%
 
535828.3%
 
123355.4%
 
820974.9%
 
618614.3%
 
218464.3%
 
415853.7%
 
714813.4%
 
312853.0%
 
ValueCountFrequency (%) 
123355.4%
 
218464.3%
 
312853.0%
 
415853.7%
 
535828.3%
 
618614.3%
 
714813.4%
 
820974.9%
 
9504511.7%
 
102184550.8%
 
ValueCountFrequency (%) 
102184550.8%
 
9504511.7%
 
820974.9%
 
714813.4%
 
618614.3%
 
535828.3%
 
415853.7%
 
312853.0%
 
218464.3%
 
123355.4%
 

D19_VERSAND_ONLINE_QUOTE_12
Real number (ℝ≥0)

MISSING
ZEROS

Distinct11
Distinct (%)< 0.1%
Missing7584
Missing (%)17.7%
Infinite0
Infinite (%)0.0%
Mean2.61620216
Minimum0
Maximum10
Zeros24597
Zeros (%)57.3%
Memory size335.8 KiB
2020-11-30T23:56:46.853872image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q36
95-th percentile10
Maximum10
Range10
Interquartile range (IQR)6

Descriptive statistics

Standard deviation4.183047724
Coefficient of variation (CV)1.598900799
Kurtosis-0.7358216122
Mean2.61620216
Median Absolute Deviation (MAD)0
Skewness1.074200242
Sum92556
Variance17.49788826
MonotocityNot monotonic
2020-11-30T23:56:46.942547image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%) 
02459757.3%
 
10749417.4%
 
59162.1%
 
84961.2%
 
34861.1%
 
74391.0%
 
92800.7%
 
12030.5%
 
21780.4%
 
61510.4%
 
41380.3%
 
(Missing)758417.7%
 
ValueCountFrequency (%) 
02459757.3%
 
12030.5%
 
21780.4%
 
34861.1%
 
41380.3%
 
59162.1%
 
61510.4%
 
74391.0%
 
84961.2%
 
92800.7%
 
ValueCountFrequency (%) 
10749417.4%
 
92800.7%
 
84961.2%
 
74391.0%
 
61510.4%
 
59162.1%
 
41380.3%
 
34861.1%
 
21780.4%
 
12030.5%
 

D19_VERSAND_REST
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.7223592943
Minimum0
Maximum7
Zeros36458
Zeros (%)84.9%
Memory size335.8 KiB
2020-11-30T23:56:47.028495image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile6
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.807373135
Coefficient of variation (CV)2.502041781
Kurtosis3.65514105
Mean0.7223592943
Median Absolute Deviation (MAD)0
Skewness2.298122007
Sum31034
Variance3.26659765
MonotocityNot monotonic
2020-11-30T23:56:47.110343image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
03645884.9%
 
630097.0%
 
317784.1%
 
510222.4%
 
22390.6%
 
71920.4%
 
41500.3%
 
11140.3%
 
ValueCountFrequency (%) 
03645884.9%
 
11140.3%
 
22390.6%
 
317784.1%
 
41500.3%
 
510222.4%
 
630097.0%
 
71920.4%
 
ValueCountFrequency (%) 
71920.4%
 
630097.0%
 
510222.4%
 
41500.3%
 
317784.1%
 
22390.6%
 
11140.3%
 
03645884.9%
 

D19_VERSI_ANZ_12
Real number (ℝ≥0)

ZEROS

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1132163307
Minimum0
Maximum6
Zeros39485
Zeros (%)91.9%
Memory size335.8 KiB
2020-11-30T23:56:47.198098image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum6
Range6
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.422899479
Coefficient of variation (CV)3.735322249
Kurtosis23.59097344
Mean0.1132163307
Median Absolute Deviation (MAD)0
Skewness4.467679767
Sum4864
Variance0.1788439694
MonotocityNot monotonic
2020-11-30T23:56:47.279110image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
03948591.9%
 
123275.4%
 
29652.2%
 
31410.3%
 
4370.1%
 
56< 0.1%
 
61< 0.1%
 
ValueCountFrequency (%) 
03948591.9%
 
123275.4%
 
29652.2%
 
31410.3%
 
4370.1%
 
56< 0.1%
 
61< 0.1%
 
ValueCountFrequency (%) 
61< 0.1%
 
56< 0.1%
 
4370.1%
 
31410.3%
 
29652.2%
 
123275.4%
 
03948591.9%
 

D19_VERSI_ANZ_24
Real number (ℝ≥0)

ZEROS

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1961966389
Minimum0
Maximum6
Zeros37473
Zeros (%)87.2%
Memory size335.8 KiB
2020-11-30T23:56:47.365772image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum6
Range6
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.58282604
Coefficient of variation (CV)2.97062194
Kurtosis14.58017382
Mean0.1961966389
Median Absolute Deviation (MAD)0
Skewness3.567704655
Sum8429
Variance0.3396861928
MonotocityNot monotonic
2020-11-30T23:56:47.444925image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
03747387.2%
 
132877.7%
 
216683.9%
 
33550.8%
 
41560.4%
 
521< 0.1%
 
62< 0.1%
 
ValueCountFrequency (%) 
03747387.2%
 
132877.7%
 
216683.9%
 
33550.8%
 
41560.4%
 
521< 0.1%
 
62< 0.1%
 
ValueCountFrequency (%) 
62< 0.1%
 
521< 0.1%
 
41560.4%
 
33550.8%
 
216683.9%
 
132877.7%
 
03747387.2%
 

D19_VERSI_DATUM
Real number (ℝ≥0)

Distinct10
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.156440575
Minimum1
Maximum10
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:56:47.533794image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5
Q110
median10
Q310
95-th percentile10
Maximum10
Range9
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.906264354
Coefficient of variation (CV)0.2081883607
Kurtosis6.062519874
Mean9.156440575
Median Absolute Deviation (MAD)0
Skewness-2.575567305
Sum393379
Variance3.633843786
MonotocityNot monotonic
2020-11-30T23:56:47.615100image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
103225675.1%
 
936118.4%
 
516373.8%
 
816063.7%
 
611102.6%
 
79022.1%
 
27501.7%
 
14161.0%
 
43750.9%
 
32990.7%
 
ValueCountFrequency (%) 
14161.0%
 
27501.7%
 
32990.7%
 
43750.9%
 
516373.8%
 
611102.6%
 
79022.1%
 
816063.7%
 
936118.4%
 
103225675.1%
 
ValueCountFrequency (%) 
103225675.1%
 
936118.4%
 
816063.7%
 
79022.1%
 
611102.6%
 
516373.8%
 
43750.9%
 
32990.7%
 
27501.7%
 
14161.0%
 

D19_VERSI_OFFLINE_DATUM
Real number (ℝ≥0)

Distinct10
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.898887389
Minimum1
Maximum10
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:56:47.699662image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile10
Q110
median10
Q310
95-th percentile10
Maximum10
Range9
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.6328669929
Coefficient of variation (CV)0.06393314401
Kurtosis55.71106942
Mean9.898887389
Median Absolute Deviation (MAD)0
Skewness-7.263246089
Sum425276
Variance0.4005206307
MonotocityNot monotonic
2020-11-30T23:56:47.782601image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
104145296.5%
 
95631.3%
 
54851.1%
 
82720.6%
 
61060.2%
 
7510.1%
 
413< 0.1%
 
39< 0.1%
 
16< 0.1%
 
25< 0.1%
 
ValueCountFrequency (%) 
16< 0.1%
 
25< 0.1%
 
39< 0.1%
 
413< 0.1%
 
54851.1%
 
61060.2%
 
7510.1%
 
82720.6%
 
95631.3%
 
104145296.5%
 
ValueCountFrequency (%) 
104145296.5%
 
95631.3%
 
82720.6%
 
7510.1%
 
61060.2%
 
54851.1%
 
413< 0.1%
 
39< 0.1%
 
25< 0.1%
 
16< 0.1%
 

D19_VERSI_ONLINE_DATUM
Real number (ℝ≥0)

SKEWED

Distinct10
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.984288441
Minimum1
Maximum10
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:56:47.870716image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile10
Q110
median10
Q310
95-th percentile10
Maximum10
Range9
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.2582136755
Coefficient of variation (CV)0.02586200079
Kurtosis462.2149483
Mean9.984288441
Median Absolute Deviation (MAD)0
Skewness-20.21632487
Sum428945
Variance0.06667430222
MonotocityNot monotonic
2020-11-30T23:56:47.953992image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
104273599.5%
 
9730.2%
 
8430.1%
 
5380.1%
 
7300.1%
 
621< 0.1%
 
411< 0.1%
 
25< 0.1%
 
34< 0.1%
 
12< 0.1%
 
ValueCountFrequency (%) 
12< 0.1%
 
25< 0.1%
 
34< 0.1%
 
411< 0.1%
 
5380.1%
 
621< 0.1%
 
7300.1%
 
8430.1%
 
9730.2%
 
104273599.5%
 
ValueCountFrequency (%) 
104273599.5%
 
9730.2%
 
8430.1%
 
7300.1%
 
621< 0.1%
 
5380.1%
 
411< 0.1%
 
34< 0.1%
 
25< 0.1%
 
12< 0.1%
 

D19_VERSI_ONLINE_QUOTE_12
Categorical

MISSING

Distinct4
Distinct (%)< 0.1%
Missing7584
Missing (%)17.7%
Memory size335.8 KiB
0
35318 
10
 
54
5
 
5
3
 
1
ValueCountFrequency (%) 
03531882.2%
 
10540.1%
 
55< 0.1%
 
31< 0.1%
 
(Missing)758417.7%
 
2020-11-30T23:56:48.053583image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique1 ?
Unique (%)< 0.1%

Overview of Unicode Properties

Unique unicode characters7
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
07075054.9%
 
.3537827.4%
 
n1516811.8%
 
a75845.9%
 
154< 0.1%
 
55< 0.1%
 
31< 0.1%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number7081054.9%
 
Other Punctuation3537827.4%
 
Lowercase Letter2275217.6%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
07075099.9%
 
1540.1%
 
55< 0.1%
 
31< 0.1%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
.35378100.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n1516866.7%
 
a758433.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Common10618882.4%
 
Latin2275217.6%
 

Most frequent Common characters

ValueCountFrequency (%) 
07075066.6%
 
.3537833.3%
 
1540.1%
 
55< 0.1%
 
31< 0.1%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n1516866.7%
 
a758433.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII128940100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
07075054.9%
 
.3537827.4%
 
n1516811.8%
 
a75845.9%
 
154< 0.1%
 
55< 0.1%
 
31< 0.1%
 

D19_VERSICHERUNGEN
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.195381965
Minimum0
Maximum7
Zeros32015
Zeros (%)74.5%
Memory size335.8 KiB
2020-11-30T23:56:48.141236image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile6
Maximum7
Range7
Interquartile range (IQR)1

Descriptive statistics

Standard deviation2.199961507
Coefficient of variation (CV)1.840383719
Kurtosis0.464544979
Mean1.195381965
Median Absolute Deviation (MAD)0
Skewness1.482638204
Sum51356
Variance4.839830632
MonotocityNot monotonic
2020-11-30T23:56:48.222189image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
03201574.5%
 
6521712.1%
 
323275.4%
 
514743.4%
 
27141.7%
 
45381.3%
 
14361.0%
 
72410.6%
 
ValueCountFrequency (%) 
03201574.5%
 
14361.0%
 
27141.7%
 
323275.4%
 
45381.3%
 
514743.4%
 
6521712.1%
 
72410.6%
 
ValueCountFrequency (%) 
72410.6%
 
6521712.1%
 
514743.4%
 
45381.3%
 
323275.4%
 
27141.7%
 
14361.0%
 
03201574.5%
 

D19_VOLLSORTIMENT
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.845374983
Minimum0
Maximum7
Zeros20628
Zeros (%)48.0%
Memory size335.8 KiB
2020-11-30T23:56:48.309022image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q36
95-th percentile7
Maximum7
Range7
Interquartile range (IQR)6

Descriptive statistics

Standard deviation2.892541053
Coefficient of variation (CV)1.016576399
Kurtosis-1.831033011
Mean2.845374983
Median Absolute Deviation (MAD)3
Skewness0.1539149855
Sum122243
Variance8.366793743
MonotocityNot monotonic
2020-11-30T23:56:48.391993image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
02062848.0%
 
61426133.2%
 
331007.2%
 
723885.6%
 
517214.0%
 
24421.0%
 
42500.6%
 
11720.4%
 
ValueCountFrequency (%) 
02062848.0%
 
11720.4%
 
24421.0%
 
331007.2%
 
42500.6%
 
517214.0%
 
61426133.2%
 
723885.6%
 
ValueCountFrequency (%) 
723885.6%
 
61426133.2%
 
517214.0%
 
42500.6%
 
331007.2%
 
24421.0%
 
11720.4%
 
02062848.0%
 

D19_WEIN_FEINKOST
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.8420930124
Minimum0
Maximum7
Zeros36950
Zeros (%)86.0%
Memory size335.8 KiB
2020-11-30T23:56:48.482212image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile6
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.123263069
Coefficient of variation (CV)2.521411575
Kurtosis2.922960589
Mean0.8420930124
Median Absolute Deviation (MAD)0
Skewness2.188275769
Sum36178
Variance4.50824606
MonotocityNot monotonic
2020-11-30T23:56:48.563486image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
03695086.0%
 
632387.5%
 
718944.4%
 
54141.0%
 
33870.9%
 
4520.1%
 
2260.1%
 
11< 0.1%
 
ValueCountFrequency (%) 
03695086.0%
 
11< 0.1%
 
2260.1%
 
33870.9%
 
4520.1%
 
54141.0%
 
632387.5%
 
718944.4%
 
ValueCountFrequency (%) 
718944.4%
 
632387.5%
 
54141.0%
 
4520.1%
 
33870.9%
 
2260.1%
 
11< 0.1%
 
03695086.0%
 

DSL_FLAG
Boolean

MISSING

Distinct2
Distinct (%)< 0.1%
Missing7777
Missing (%)18.1%
Memory size335.8 KiB
1
34500 
0
 
685
(Missing)
7777 
ValueCountFrequency (%) 
13450080.3%
 
06851.6%
 
(Missing)777718.1%
 

EINGEFUEGT_AM
Categorical

HIGH CARDINALITY
MISSING

Distinct1599
Distinct (%)4.5%
Missing7777
Missing (%)18.1%
Memory size335.8 KiB
1992-02-10 00:00:00
18156 
1992-02-12 00:00:00
8167 
1995-02-07 00:00:00
 
519
1993-03-01 00:00:00
 
249
2003-11-18 00:00:00
 
215
Other values (1594)
7879 
ValueCountFrequency (%) 
1992-02-10 00:00:001815642.3%
 
1992-02-12 00:00:00816719.0%
 
1995-02-07 00:00:005191.2%
 
1993-03-01 00:00:002490.6%
 
2003-11-18 00:00:002150.5%
 
2005-12-16 00:00:001490.3%
 
1995-10-17 00:00:001110.3%
 
1993-09-21 00:00:00980.2%
 
1994-02-03 00:00:00930.2%
 
2004-04-14 00:00:00920.2%
 
1993-09-22 00:00:00770.2%
 
1992-02-21 00:00:00660.2%
 
1995-10-10 00:00:00650.2%
 
2000-05-10 00:00:00610.1%
 
2005-04-15 00:00:00590.1%
 
1994-12-13 00:00:00550.1%
 
1995-10-18 00:00:00510.1%
 
1993-09-23 00:00:00470.1%
 
1993-10-21 00:00:00460.1%
 
1993-03-23 00:00:00450.1%
 
1996-01-26 00:00:00450.1%
 
1993-04-01 00:00:00450.1%
 
2005-08-23 00:00:00440.1%
 
1995-07-19 00:00:00430.1%
 
1994-05-19 00:00:00420.1%
 
Other values (1574)654515.2%
 
(Missing)777718.1%
 
2020-11-30T23:56:48.697878image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique683 ?
Unique (%)1.9%

Overview of Unicode Properties

Unique unicode characters15
Unique unicode categories5 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
027047439.1%
 
-7037010.2%
 
:7037010.2%
 
2684919.9%
 
9682969.9%
 
1673839.7%
 
351855.1%
 
n155542.2%
 
a77771.1%
 
338570.6%
 
534630.5%
 
432720.5%
 
728990.4%
 
626390.4%
 
818160.3%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number49259071.2%
 
Dash Punctuation7037010.2%
 
Other Punctuation7037010.2%
 
Space Separator351855.1%
 
Lowercase Letter233313.4%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
027047454.9%
 
26849113.9%
 
96829613.9%
 
16738313.7%
 
338570.8%
 
534630.7%
 
432720.7%
 
728990.6%
 
626390.5%
 
818160.4%
 

Most frequent Dash Punctuation characters

ValueCountFrequency (%) 
-70370100.0%
 

Most frequent Space Separator characters

ValueCountFrequency (%) 
35185100.0%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
:70370100.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n1555466.7%
 
a777733.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Common66851596.6%
 
Latin233313.4%
 

Most frequent Common characters

ValueCountFrequency (%) 
027047440.5%
 
-7037010.5%
 
:7037010.5%
 
26849110.2%
 
96829610.2%
 
16738310.1%
 
351855.3%
 
338570.6%
 
534630.5%
 
432720.5%
 
728990.4%
 
626390.4%
 
818160.3%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n1555466.7%
 
a777733.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII691846100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
027047439.1%
 
-7037010.2%
 
:7037010.2%
 
2684919.9%
 
9682969.9%
 
1673839.7%
 
351855.1%
 
n155542.2%
 
a77771.1%
 
338570.6%
 
534630.5%
 
432720.5%
 
728990.4%
 
626390.4%
 
818160.3%
 

EINGEZOGENAM_HH_JAHR
Real number (ℝ≥0)

MISSING

Distinct33
Distinct (%)0.1%
Missing6969
Missing (%)16.2%
Infinite0
Infinite (%)0.0%
Mean1998.87367
Minimum1986
Maximum2018
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:56:48.816919image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1986
5-th percentile1994
Q11994
median1997
Q32002
95-th percentile2011
Maximum2018
Range32
Interquartile range (IQR)8

Descriptive statistics

Standard deviation5.776401974
Coefficient of variation (CV)0.002889828437
Kurtosis0.2697256702
Mean1998.87367
Median Absolute Deviation (MAD)3
Skewness1.102881098
Sum71945460
Variance33.36681976
MonotocityNot monotonic
2020-11-30T23:56:48.921445image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%) 
19941439733.5%
 
1997515412.0%
 
200420114.7%
 
200113493.1%
 
199913483.1%
 
199813253.1%
 
200012873.0%
 
200212032.8%
 
200711022.6%
 
20088301.9%
 
20036771.6%
 
20056001.4%
 
20065731.3%
 
19965321.2%
 
20154881.1%
 
20094701.1%
 
20114261.0%
 
20144121.0%
 
19953950.9%
 
20123940.9%
 
20103890.9%
 
20133810.9%
 
1993770.2%
 
1992450.1%
 
1991330.1%
 
Other values (8)950.2%
 
(Missing)696916.2%
 
ValueCountFrequency (%) 
19861< 0.1%
 
19872< 0.1%
 
19883< 0.1%
 
198916< 0.1%
 
1990220.1%
 
1991330.1%
 
1992450.1%
 
1993770.2%
 
19941439733.5%
 
19953950.9%
 
ValueCountFrequency (%) 
2018270.1%
 
20176< 0.1%
 
201618< 0.1%
 
20154881.1%
 
20144121.0%
 
20133810.9%
 
20123940.9%
 
20114261.0%
 
20103890.9%
 
20094701.1%
 

EWDICHTE
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing7799
Missing (%)18.2%
Infinite0
Infinite (%)0.0%
Mean3.78696357
Minimum1
Maximum6
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:56:49.016262image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median4
Q35
95-th percentile6
Maximum6
Range5
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.735390185
Coefficient of variation (CV)0.458253731
Kurtosis-1.331905684
Mean3.78696357
Median Absolute Deviation (MAD)2
Skewness-0.1889670668
Sum133161
Variance3.011579094
MonotocityNot monotonic
2020-11-30T23:56:49.102622image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
6791818.4%
 
2672115.6%
 
5672015.6%
 
4573513.3%
 
142689.9%
 
338018.8%
 
(Missing)779918.2%
 
ValueCountFrequency (%) 
142689.9%
 
2672115.6%
 
338018.8%
 
4573513.3%
 
5672015.6%
 
6791818.4%
 
ValueCountFrequency (%) 
6791818.4%
 
5672015.6%
 
4573513.3%
 
338018.8%
 
2672115.6%
 
142689.9%
 

EXTSEL992
Real number (ℝ≥0)

MISSING

Distinct56
Distinct (%)0.2%
Missing15948
Missing (%)37.1%
Infinite0
Infinite (%)0.0%
Mean42.68434886
Minimum1
Maximum56
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:56:49.206922image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile18
Q134
median47
Q355
95-th percentile56
Maximum56
Range55
Interquartile range (IQR)21

Descriptive statistics

Standard deviation13.56158044
Coefficient of variation (CV)0.3177178709
Kurtosis-0.02078671672
Mean42.68434886
Median Absolute Deviation (MAD)9
Skewness-0.8364997453
Sum1153075
Variance183.916464
MonotocityNot monotonic
2020-11-30T23:56:49.316290image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
56619514.4%
 
5525075.8%
 
3614073.3%
 
3112813.0%
 
5412322.9%
 
3512272.9%
 
5011772.7%
 
5311502.7%
 
349402.2%
 
237311.7%
 
387231.7%
 
277181.7%
 
415981.4%
 
485541.3%
 
395301.2%
 
374040.9%
 
463580.8%
 
473410.8%
 
403400.8%
 
523280.8%
 
263040.7%
 
332910.7%
 
432810.7%
 
292790.6%
 
212560.6%
 
Other values (31)28626.7%
 
(Missing)1594837.1%
 
ValueCountFrequency (%) 
1590.1%
 
21380.3%
 
31380.3%
 
4470.1%
 
5510.1%
 
62070.5%
 
714< 0.1%
 
815< 0.1%
 
9570.1%
 
10470.1%
 
ValueCountFrequency (%) 
56619514.4%
 
5525075.8%
 
5412322.9%
 
5311502.7%
 
523280.8%
 
51960.2%
 
5011772.7%
 
49230.1%
 
485541.3%
 
473410.8%
 

FINANZ_ANLEGER
Real number (ℝ≥0)

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.372026442
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:56:49.413524image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.544878868
Coefficient of variation (CV)0.6512907446
Kurtosis-1.027864772
Mean2.372026442
Median Absolute Deviation (MAD)1
Skewness0.7267218327
Sum101907
Variance2.386650715
MonotocityNot monotonic
2020-11-30T23:56:49.543172image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
11861243.3%
 
2906521.1%
 
5832619.4%
 
3430110.0%
 
426586.2%
 
ValueCountFrequency (%) 
11861243.3%
 
2906521.1%
 
3430110.0%
 
426586.2%
 
5832619.4%
 
ValueCountFrequency (%) 
5832619.4%
 
426586.2%
 
3430110.0%
 
2906521.1%
 
11861243.3%
 

FINANZ_HAUSBAUER
Real number (ℝ≥0)

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.221963596
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:56:49.640182image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.283686745
Coefficient of variation (CV)0.3984175199
Kurtosis-1.030987674
Mean3.221963596
Median Absolute Deviation (MAD)1
Skewness-0.02137573192
Sum138422
Variance1.64785166
MonotocityNot monotonic
2020-11-30T23:56:49.725794image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31407432.8%
 
51034824.1%
 
2836119.5%
 
4585313.6%
 
1432610.1%
 
ValueCountFrequency (%) 
1432610.1%
 
2836119.5%
 
31407432.8%
 
4585313.6%
 
51034824.1%
 
ValueCountFrequency (%) 
51034824.1%
 
4585313.6%
 
31407432.8%
 
2836119.5%
 
1432610.1%
 

FINANZ_MINIMALIST
Real number (ℝ≥0)

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.743005447
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:56:49.816729image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median4
Q35
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.090230172
Coefficient of variation (CV)0.2912713293
Kurtosis-1.016818132
Mean3.743005447
Median Absolute Deviation (MAD)1
Skewness-0.2620273157
Sum160807
Variance1.188601828
MonotocityNot monotonic
2020-11-30T23:56:49.902611image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
51476434.4%
 
31429733.3%
 
4845119.7%
 
2484211.3%
 
16081.4%
 
ValueCountFrequency (%) 
16081.4%
 
2484211.3%
 
31429733.3%
 
4845119.7%
 
51476434.4%
 
ValueCountFrequency (%) 
51476434.4%
 
4845119.7%
 
31429733.3%
 
2484211.3%
 
16081.4%
 

FINANZ_SPARER
Real number (ℝ≥0)

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.858991667
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:56:49.993878image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q33
95-th percentile4
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.235721471
Coefficient of variation (CV)0.6647267402
Kurtosis-0.5294347268
Mean1.858991667
Median Absolute Deviation (MAD)0
Skewness1.047320705
Sum79866
Variance1.527007554
MonotocityNot monotonic
2020-11-30T23:56:50.075180image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
12636061.4%
 
4804618.7%
 
2558013.0%
 
323595.5%
 
56171.4%
 
ValueCountFrequency (%) 
12636061.4%
 
2558013.0%
 
323595.5%
 
4804618.7%
 
56171.4%
 
ValueCountFrequency (%) 
56171.4%
 
4804618.7%
 
323595.5%
 
2558013.0%
 
12636061.4%
 

FINANZ_UNAUFFAELLIGER
Real number (ℝ≥0)

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.257413528
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:56:50.163197image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q33
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.497561807
Coefficient of variation (CV)0.663397197
Kurtosis-0.6447710918
Mean2.257413528
Median Absolute Deviation (MAD)1
Skewness0.9218843122
Sum96983
Variance2.242691366
MonotocityNot monotonic
2020-11-30T23:56:50.249238image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
11917744.6%
 
21048324.4%
 
5795718.5%
 
3432510.1%
 
410202.4%
 
ValueCountFrequency (%) 
11917744.6%
 
21048324.4%
 
3432510.1%
 
410202.4%
 
5795718.5%
 
ValueCountFrequency (%) 
5795718.5%
 
410202.4%
 
3432510.1%
 
21048324.4%
 
11917744.6%
 

FINANZ_VORSORGER
Real number (ℝ≥0)

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.259485126
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:56:50.341890image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q13
median5
Q35
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation0.984685931
Coefficient of variation (CV)0.2311748725
Kurtosis0.6147583771
Mean4.259485126
Median Absolute Deviation (MAD)0
Skewness-1.144627133
Sum182996
Variance0.9696063828
MonotocityNot monotonic
2020-11-30T23:56:50.423856image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
52452457.1%
 
3921521.4%
 
4755717.6%
 
28371.9%
 
18291.9%
 
ValueCountFrequency (%) 
18291.9%
 
28371.9%
 
3921521.4%
 
4755717.6%
 
52452457.1%
 
ValueCountFrequency (%) 
52452457.1%
 
4755717.6%
 
3921521.4%
 
28371.9%
 
18291.9%
 

FINANZTYP
Real number (ℝ≥0)

Distinct6
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.27047158
Minimum1
Maximum6
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:56:50.511095image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q12
median5
Q36
95-th percentile6
Maximum6
Range5
Interquartile range (IQR)4

Descriptive statistics

Standard deviation1.668446465
Coefficient of variation (CV)0.3906937288
Kurtosis-1.304985555
Mean4.27047158
Median Absolute Deviation (MAD)1
Skewness-0.4494843445
Sum183468
Variance2.783713606
MonotocityNot monotonic
2020-11-30T23:56:50.596767image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
61505835.0%
 
21079125.1%
 
5758517.7%
 
4744717.3%
 
112092.8%
 
38722.0%
 
ValueCountFrequency (%) 
112092.8%
 
21079125.1%
 
38722.0%
 
4744717.3%
 
5758517.7%
 
61505835.0%
 
ValueCountFrequency (%) 
61505835.0%
 
5758517.7%
 
4744717.3%
 
38722.0%
 
21079125.1%
 
112092.8%
 

FIRMENDICHTE
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7777
Missing (%)18.1%
Infinite0
Infinite (%)0.0%
Mean3.562313486
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:56:50.681234image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median4
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.091114372
Coefficient of variation (CV)0.3062937545
Kurtosis-0.5572729187
Mean3.562313486
Median Absolute Deviation (MAD)1
Skewness-0.4616224196
Sum125340
Variance1.190530573
MonotocityNot monotonic
2020-11-30T23:56:50.764484image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
41300530.3%
 
3825419.2%
 
5735017.1%
 
2523212.2%
 
113443.1%
 
(Missing)777718.1%
 
ValueCountFrequency (%) 
113443.1%
 
2523212.2%
 
3825419.2%
 
41300530.3%
 
5735017.1%
 
ValueCountFrequency (%) 
5735017.1%
 
41300530.3%
 
3825419.2%
 
2523212.2%
 
113443.1%
 

GEBAEUDETYP
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing7777
Missing (%)18.1%
Infinite0
Infinite (%)0.0%
Mean2.52860594
Minimum1
Maximum8
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:56:50.852910image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q33
95-th percentile8
Maximum8
Range7
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.517929443
Coefficient of variation (CV)0.9957777144
Kurtosis0.6654017961
Mean2.52860594
Median Absolute Deviation (MAD)0
Skewness1.507798841
Sum88969
Variance6.339968682
MonotocityNot monotonic
2020-11-30T23:56:50.932619image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
12226051.8%
 
3675315.7%
 
8564213.1%
 
24361.0%
 
4610.1%
 
6330.1%
 
(Missing)777718.1%
 
ValueCountFrequency (%) 
12226051.8%
 
24361.0%
 
3675315.7%
 
4610.1%
 
6330.1%
 
8564213.1%
 
ValueCountFrequency (%) 
8564213.1%
 
6330.1%
 
4610.1%
 
3675315.7%
 
24361.0%
 
12226051.8%
 

GEBAEUDETYP_RASTER
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7777
Missing (%)18.1%
Infinite0
Infinite (%)0.0%
Mean3.807616882
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:56:51.018031image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median4
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.8823911293
Coefficient of variation (CV)0.231743675
Kurtosis0.4021013406
Mean3.807616882
Median Absolute Deviation (MAD)1
Skewness-0.6404895008
Sum133971
Variance0.7786141051
MonotocityNot monotonic
2020-11-30T23:56:51.104184image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
41681539.1%
 
3843619.6%
 
5735017.1%
 
220694.8%
 
15151.2%
 
(Missing)777718.1%
 
ValueCountFrequency (%) 
15151.2%
 
220694.8%
 
3843619.6%
 
41681539.1%
 
5735017.1%
 
ValueCountFrequency (%) 
5735017.1%
 
41681539.1%
 
3843619.6%
 
220694.8%
 
15151.2%
 

GEBURTSJAHR
Real number (ℝ≥0)

ZEROS

Distinct108
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1155.7056
Minimum0
Maximum2017
Zeros17475
Zeros (%)40.7%
Memory size335.8 KiB
2020-11-30T23:56:51.219738image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1934
Q31949
95-th percentile1970
Maximum2017
Range2017
Interquartile range (IQR)1949

Descriptive statistics

Standard deviation957.0475869
Coefficient of variation (CV)0.8281067312
Kurtosis-1.855674476
Mean1155.7056
Median Absolute Deviation (MAD)29
Skewness-0.3792022153
Sum49651424
Variance915940.0837
MonotocityNot monotonic
2020-11-30T23:56:51.344176image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
01747540.7%
 
19419182.1%
 
19398712.0%
 
19408472.0%
 
19387911.8%
 
19367311.7%
 
19357101.7%
 
19436941.6%
 
19426921.6%
 
19376821.6%
 
19446701.6%
 
19506061.4%
 
19346011.4%
 
19515861.4%
 
19525631.3%
 
19495621.3%
 
19475571.3%
 
19535481.3%
 
19485341.2%
 
19545231.2%
 
19565071.2%
 
19335001.2%
 
19454911.1%
 
19464791.1%
 
19574721.1%
 
Other values (83)1035224.1%
 
ValueCountFrequency (%) 
01747540.7%
 
19051< 0.1%
 
19081< 0.1%
 
19092< 0.1%
 
19101< 0.1%
 
19113< 0.1%
 
19121< 0.1%
 
19137< 0.1%
 
19143< 0.1%
 
19157< 0.1%
 
ValueCountFrequency (%) 
20174< 0.1%
 
20164< 0.1%
 
201510< 0.1%
 
20144< 0.1%
 
20136< 0.1%
 
20129< 0.1%
 
20111< 0.1%
 
20101< 0.1%
 
20092< 0.1%
 
20081< 0.1%
 

GEMEINDETYP
Real number (ℝ≥0)

MISSING

Distinct7
Distinct (%)< 0.1%
Missing7955
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean25.25286371
Minimum11
Maximum50
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:56:51.456142image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum11
5-th percentile11
Q112
median22
Q340
95-th percentile50
Maximum50
Range39
Interquartile range (IQR)28

Descriptive statistics

Standard deviation12.54814148
Coefficient of variation (CV)0.4968997428
Kurtosis-0.9216244006
Mean25.25286371
Median Absolute Deviation (MAD)10
Skewness0.4845956535
Sum884027
Variance157.4558547
MonotocityNot monotonic
2020-11-30T23:56:51.539891image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
11698716.3%
 
22646615.1%
 
40602014.0%
 
30576113.4%
 
12428210.0%
 
5029176.8%
 
2125746.0%
 
(Missing)795518.5%
 
ValueCountFrequency (%) 
11698716.3%
 
12428210.0%
 
2125746.0%
 
22646615.1%
 
30576113.4%
 
40602014.0%
 
5029176.8%
 
ValueCountFrequency (%) 
5029176.8%
 
40602014.0%
 
30576113.4%
 
22646615.1%
 
2125746.0%
 
12428210.0%
 
11698716.3%
 

GFK_URLAUBERTYP
Real number (ℝ≥0)

MISSING

Distinct12
Distinct (%)< 0.1%
Missing605
Missing (%)1.4%
Infinite0
Infinite (%)0.0%
Mean6.514531246
Minimum1
Maximum12
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:56:51.632634image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q14
median6
Q39
95-th percentile12
Maximum12
Range11
Interquartile range (IQR)5

Descriptive statistics

Standard deviation3.017390282
Coefficient of variation (CV)0.4631784188
Kurtosis-0.9985352663
Mean6.514531246
Median Absolute Deviation (MAD)2
Skewness0.1679486803
Sum275936
Variance9.104644112
MonotocityNot monotonic
2020-11-30T23:56:51.714922image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%) 
5981222.8%
 
10607014.1%
 
8430110.0%
 
4428110.0%
 
338038.9%
 
734208.0%
 
1224505.7%
 
1120454.8%
 
118384.3%
 
616533.8%
 
914683.4%
 
212162.8%
 
(Missing)6051.4%
 
ValueCountFrequency (%) 
118384.3%
 
212162.8%
 
338038.9%
 
4428110.0%
 
5981222.8%
 
616533.8%
 
734208.0%
 
8430110.0%
 
914683.4%
 
10607014.1%
 
ValueCountFrequency (%) 
1224505.7%
 
1120454.8%
 
10607014.1%
 
914683.4%
 
8430110.0%
 
734208.0%
 
616533.8%
 
5981222.8%
 
4428110.0%
 
338038.9%
 
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size335.8 KiB
0
30939 
1
12023 
ValueCountFrequency (%) 
03093972.0%
 
11202328.0%
 

HEALTH_TYP
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size335.8 KiB
2
17053 
1
10519 
3
7993 
-1
7397 
ValueCountFrequency (%) 
21705339.7%
 
11051924.5%
 
3799318.6%
 
-1739717.2%
 
2020-11-30T23:56:51.812599image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters4
Unique unicode categories2 ?
Unique unicode scripts1 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
11791635.6%
 
21705333.9%
 
3799315.9%
 
-739714.7%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number4296285.3%
 
Dash Punctuation739714.7%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
11791641.7%
 
21705339.7%
 
3799318.6%
 

Most frequent Dash Punctuation characters

ValueCountFrequency (%) 
-7397100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Common50359100.0%
 

Most frequent Common characters

ValueCountFrequency (%) 
11791635.6%
 
21705333.9%
 
3799315.9%
 
-739714.7%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII50359100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
11791635.6%
 
21705333.9%
 
3799315.9%
 
-739714.7%
 

HH_DELTA_FLAG
Boolean

MISSING

Distinct2
Distinct (%)< 0.1%
Missing9678
Missing (%)22.5%
Memory size335.8 KiB
0
28993 
1
4291 
(Missing)
9678 
ValueCountFrequency (%) 
02899367.5%
 
1429110.0%
 
(Missing)967822.5%
 

HH_EINKOMMEN_SCORE
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing704
Missing (%)1.6%
Infinite0
Infinite (%)0.0%
Mean3.559113067
Minimum1
Maximum6
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:56:51.894256image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median4
Q35
95-th percentile6
Maximum6
Range5
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.657999028
Coefficient of variation (CV)0.4658461242
Kurtosis-1.332669251
Mean3.559113067
Median Absolute Deviation (MAD)2
Skewness0.04993306401
Sum150401
Variance2.748960777
MonotocityNot monotonic
2020-11-30T23:56:51.978389image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
21127326.2%
 
5783518.2%
 
6695816.2%
 
4695016.2%
 
3494511.5%
 
1429710.0%
 
(Missing)7041.6%
 
ValueCountFrequency (%) 
1429710.0%
 
21127326.2%
 
3494511.5%
 
4695016.2%
 
5783518.2%
 
6695816.2%
 
ValueCountFrequency (%) 
6695816.2%
 
5783518.2%
 
4695016.2%
 
3494511.5%
 
21127326.2%
 
1429710.0%
 

INNENSTADT
Real number (ℝ≥0)

MISSING

Distinct8
Distinct (%)< 0.1%
Missing7799
Missing (%)18.2%
Infinite0
Infinite (%)0.0%
Mean4.739129198
Minimum1
Maximum8
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:56:52.059135image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median5
Q36
95-th percentile8
Maximum8
Range7
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.01026907
Coefficient of variation (CV)0.4241853273
Kurtosis-0.918889531
Mean4.739129198
Median Absolute Deviation (MAD)1
Skewness-0.02683364011
Sum166642
Variance4.041181734
MonotocityNot monotonic
2020-11-30T23:56:52.142912image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
5647515.1%
 
4595013.8%
 
6521312.1%
 
242349.9%
 
841929.8%
 
339909.3%
 
733517.8%
 
117584.1%
 
(Missing)779918.2%
 
ValueCountFrequency (%) 
117584.1%
 
242349.9%
 
339909.3%
 
4595013.8%
 
5647515.1%
 
6521312.1%
 
733517.8%
 
841929.8%
 
ValueCountFrequency (%) 
841929.8%
 
733517.8%
 
6521312.1%
 
5647515.1%
 
4595013.8%
 
339909.3%
 
242349.9%
 
117584.1%
 

KBA05_ALTER1
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing8648
Missing (%)20.1%
Infinite0
Infinite (%)0.0%
Mean1.801859299
Minimum0
Maximum9
Zeros5246
Zeros (%)12.2%
Memory size335.8 KiB
2020-11-30T23:56:52.231408image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q33
95-th percentile4
Maximum9
Range9
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.340189404
Coefficient of variation (CV)0.7437813841
Kurtosis7.342953579
Mean1.801859299
Median Absolute Deviation (MAD)1
Skewness1.678734062
Sum61829
Variance1.796107638
MonotocityNot monotonic
2020-11-30T23:56:52.307733image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
21112625.9%
 
1921821.5%
 
3645215.0%
 
0524612.2%
 
418894.4%
 
93830.9%
 
(Missing)864820.1%
 
ValueCountFrequency (%) 
0524612.2%
 
1921821.5%
 
21112625.9%
 
3645215.0%
 
418894.4%
 
93830.9%
 
ValueCountFrequency (%) 
93830.9%
 
418894.4%
 
3645215.0%
 
21112625.9%
 
1921821.5%
 
0524612.2%
 

KBA05_ALTER2
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing8648
Missing (%)20.1%
Infinite0
Infinite (%)0.0%
Mean2.901410503
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:56:52.387104image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q33
95-th percentile5
Maximum9
Range8
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.199741952
Coefficient of variation (CV)0.4135030017
Kurtosis5.794001462
Mean2.901410503
Median Absolute Deviation (MAD)1
Skewness1.406381264
Sum99559
Variance1.439380752
MonotocityNot monotonic
2020-11-30T23:56:52.471177image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31369531.9%
 
2894920.8%
 
4605414.1%
 
133137.7%
 
519204.5%
 
93830.9%
 
(Missing)864820.1%
 
ValueCountFrequency (%) 
133137.7%
 
2894920.8%
 
31369531.9%
 
4605414.1%
 
519204.5%
 
93830.9%
 
ValueCountFrequency (%) 
93830.9%
 
519204.5%
 
4605414.1%
 
31369531.9%
 
2894920.8%
 
133137.7%
 

KBA05_ALTER3
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing8648
Missing (%)20.1%
Infinite0
Infinite (%)0.0%
Mean3.138252608
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:56:52.560155image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum9
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.204453234
Coefficient of variation (CV)0.3837974135
Kurtosis4.696540955
Mean3.138252608
Median Absolute Deviation (MAD)1
Skewness1.147877142
Sum107686
Variance1.450707593
MonotocityNot monotonic
2020-11-30T23:56:52.642081image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31390532.4%
 
4773618.0%
 
2675015.7%
 
531357.3%
 
124055.6%
 
93830.9%
 
(Missing)864820.1%
 
ValueCountFrequency (%) 
124055.6%
 
2675015.7%
 
31390532.4%
 
4773618.0%
 
531357.3%
 
93830.9%
 
ValueCountFrequency (%) 
93830.9%
 
531357.3%
 
4773618.0%
 
31390532.4%
 
2675015.7%
 
124055.6%
 

KBA05_ALTER4
Real number (ℝ≥0)

MISSING
ZEROS

Distinct7
Distinct (%)< 0.1%
Missing8648
Missing (%)20.1%
Infinite0
Infinite (%)0.0%
Mean3.220726234
Minimum0
Maximum9
Zeros830
Zeros (%)1.9%
Memory size335.8 KiB
2020-11-30T23:56:52.733431image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q13
median3
Q34
95-th percentile5
Maximum9
Range9
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.260912146
Coefficient of variation (CV)0.3914993249
Kurtosis4.004983825
Mean3.220726234
Median Absolute Deviation (MAD)1
Skewness0.6557965059
Sum110516
Variance1.589899441
MonotocityNot monotonic
2020-11-30T23:56:52.810655image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
31433033.4%
 
4831619.4%
 
2505611.8%
 
538268.9%
 
115733.7%
 
08301.9%
 
93830.9%
 
(Missing)864820.1%
 
ValueCountFrequency (%) 
08301.9%
 
115733.7%
 
2505611.8%
 
31433033.4%
 
4831619.4%
 
538268.9%
 
93830.9%
 
ValueCountFrequency (%) 
93830.9%
 
538268.9%
 
4831619.4%
 
31433033.4%
 
2505611.8%
 
115733.7%
 
08301.9%
 

KBA05_ANHANG
Real number (ℝ≥0)

MISSING
ZEROS

Distinct5
Distinct (%)< 0.1%
Missing8648
Missing (%)20.1%
Infinite0
Infinite (%)0.0%
Mean1.191787609
Minimum0
Maximum9
Zeros9912
Zeros (%)23.1%
Memory size335.8 KiB
2020-11-30T23:56:52.891925image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile3
Maximum9
Range9
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.265855876
Coefficient of variation (CV)1.062148882
Kurtosis13.06354412
Mean1.191787609
Median Absolute Deviation (MAD)1
Skewness2.665656716
Sum40895
Variance1.602391098
MonotocityNot monotonic
2020-11-30T23:56:52.972450image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
11524835.5%
 
0991223.1%
 
3481211.2%
 
239819.3%
 
93610.8%
 
(Missing)864820.1%
 
ValueCountFrequency (%) 
0991223.1%
 
11524835.5%
 
239819.3%
 
3481211.2%
 
93610.8%
 
ValueCountFrequency (%) 
93610.8%
 
3481211.2%
 
239819.3%
 
11524835.5%
 
0991223.1%
 

KBA05_ANTG1
Real number (ℝ≥0)

MISSING
ZEROS

Distinct5
Distinct (%)< 0.1%
Missing8648
Missing (%)20.1%
Infinite0
Infinite (%)0.0%
Mean1.848574926
Minimum0
Maximum4
Zeros9114
Zeros (%)21.2%
Memory size335.8 KiB
2020-11-30T23:56:53.051218image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q33
95-th percentile4
Maximum4
Range4
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.449277392
Coefficient of variation (CV)0.7839971058
Kurtosis-1.357388562
Mean1.848574926
Median Absolute Deviation (MAD)1
Skewness0.08200770612
Sum63432
Variance2.100404958
MonotocityNot monotonic
2020-11-30T23:56:53.130528image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
0911421.2%
 
3692416.1%
 
2659115.3%
 
4593113.8%
 
1575413.4%
 
(Missing)864820.1%
 
ValueCountFrequency (%) 
0911421.2%
 
1575413.4%
 
2659115.3%
 
3692416.1%
 
4593113.8%
 
ValueCountFrequency (%) 
4593113.8%
 
3692416.1%
 
2659115.3%
 
1575413.4%
 
0911421.2%
 

KBA05_ANTG2
Real number (ℝ≥0)

MISSING
ZEROS

Distinct5
Distinct (%)< 0.1%
Missing8648
Missing (%)20.1%
Infinite0
Infinite (%)0.0%
Mean1.171941482
Minimum0
Maximum4
Zeros12918
Zeros (%)30.1%
Memory size335.8 KiB
2020-11-30T23:56:53.219565image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile3
Maximum4
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.156451788
Coefficient of variation (CV)0.9867828779
Kurtosis-0.7064772493
Mean1.171941482
Median Absolute Deviation (MAD)1
Skewness0.6256106174
Sum40214
Variance1.337380738
MonotocityNot monotonic
2020-11-30T23:56:53.302058image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
01291830.1%
 
1922221.5%
 
2647015.1%
 
3476411.1%
 
49402.2%
 
(Missing)864820.1%
 
ValueCountFrequency (%) 
01291830.1%
 
1922221.5%
 
2647015.1%
 
3476411.1%
 
49402.2%
 
ValueCountFrequency (%) 
49402.2%
 
3476411.1%
 
2647015.1%
 
1922221.5%
 
01291830.1%
 

KBA05_ANTG3
Categorical

MISSING

Distinct4
Distinct (%)< 0.1%
Missing8648
Missing (%)20.1%
Memory size335.8 KiB
0
26001 
1
2907 
3
2707 
2
2699 
ValueCountFrequency (%) 
02600160.5%
 
129076.8%
 
327076.3%
 
226996.3%
 
(Missing)864820.1%
 
2020-11-30T23:56:53.401312image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters7
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
06031546.8%
 
.3431426.6%
 
n1729613.4%
 
a86486.7%
 
129072.3%
 
327072.1%
 
226992.1%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number6862853.2%
 
Other Punctuation3431426.6%
 
Lowercase Letter2594420.1%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
06031587.9%
 
129074.2%
 
327073.9%
 
226993.9%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
.34314100.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n1729666.7%
 
a864833.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Common10294279.9%
 
Latin2594420.1%
 

Most frequent Common characters

ValueCountFrequency (%) 
06031558.6%
 
.3431433.3%
 
129072.8%
 
327072.6%
 
226992.6%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n1729666.7%
 
a864833.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII128886100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
06031546.8%
 
.3431426.6%
 
n1729613.4%
 
a86486.7%
 
129072.3%
 
327072.1%
 
226992.1%
 

KBA05_ANTG4
Categorical

MISSING

Distinct3
Distinct (%)< 0.1%
Missing8648
Missing (%)20.1%
Memory size335.8 KiB
0
29002 
2
 
2702
1
 
2610
ValueCountFrequency (%) 
02900267.5%
 
227026.3%
 
126106.1%
 
(Missing)864820.1%
 
2020-11-30T23:56:53.499770image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters6
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
06331649.1%
 
.3431426.6%
 
n1729613.4%
 
a86486.7%
 
227022.1%
 
126102.0%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number6862853.2%
 
Other Punctuation3431426.6%
 
Lowercase Letter2594420.1%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
06331692.3%
 
227023.9%
 
126103.8%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
.34314100.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n1729666.7%
 
a864833.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Common10294279.9%
 
Latin2594420.1%
 

Most frequent Common characters

ValueCountFrequency (%) 
06331661.5%
 
.3431433.3%
 
227022.6%
 
126102.5%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n1729666.7%
 
a864833.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII128886100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
06331649.1%
 
.3431426.6%
 
n1729613.4%
 
a86486.7%
 
227022.1%
 
126102.0%
 

KBA05_AUTOQUOT
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing8648
Missing (%)20.1%
Infinite0
Infinite (%)0.0%
Mean3.420644635
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:56:53.584499image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median3
Q34
95-th percentile5
Maximum9
Range8
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.22936339
Coefficient of variation (CV)0.3593952371
Kurtosis3.365315051
Mean3.420644635
Median Absolute Deviation (MAD)1
Skewness0.6767172155
Sum117376
Variance1.511334344
MonotocityNot monotonic
2020-11-30T23:56:53.664748image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31154526.9%
 
41092325.4%
 
5498211.6%
 
242119.8%
 
122705.3%
 
93830.9%
 
(Missing)864820.1%
 
ValueCountFrequency (%) 
122705.3%
 
242119.8%
 
31154526.9%
 
41092325.4%
 
5498211.6%
 
93830.9%
 
ValueCountFrequency (%) 
93830.9%
 
5498211.6%
 
41092325.4%
 
31154526.9%
 
242119.8%
 
122705.3%
 

KBA05_BAUMAX
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing8648
Missing (%)20.1%
Infinite0
Infinite (%)0.0%
Mean1.220726234
Minimum0
Maximum5
Zeros14332
Zeros (%)33.4%
Memory size335.8 KiB
2020-11-30T23:56:53.750960image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q31
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.58808825
Coefficient of variation (CV)1.300937267
Kurtosis0.7005542379
Mean1.220726234
Median Absolute Deviation (MAD)1
Skewness1.405282847
Sum41888
Variance2.522024291
MonotocityNot monotonic
2020-11-30T23:56:53.836252image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
01433233.4%
 
11282929.9%
 
533177.7%
 
322385.2%
 
412823.0%
 
23160.7%
 
(Missing)864820.1%
 
ValueCountFrequency (%) 
01433233.4%
 
11282929.9%
 
23160.7%
 
322385.2%
 
412823.0%
 
533177.7%
 
ValueCountFrequency (%) 
533177.7%
 
412823.0%
 
322385.2%
 
23160.7%
 
11282929.9%
 
01433233.4%
 

KBA05_CCM1
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing8648
Missing (%)20.1%
Infinite0
Infinite (%)0.0%
Mean2.992597774
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:56:53.920017image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum9
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.204404722
Coefficient of variation (CV)0.402461277
Kurtosis5.289976708
Mean2.992597774
Median Absolute Deviation (MAD)1
Skewness1.315301334
Sum102688
Variance1.450590733
MonotocityNot monotonic
2020-11-30T23:56:54.002488image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31389132.3%
 
2823219.2%
 
4649215.1%
 
128616.7%
 
524555.7%
 
93830.9%
 
(Missing)864820.1%
 
ValueCountFrequency (%) 
128616.7%
 
2823219.2%
 
31389132.3%
 
4649215.1%
 
524555.7%
 
93830.9%
 
ValueCountFrequency (%) 
93830.9%
 
524555.7%
 
4649215.1%
 
31389132.3%
 
2823219.2%
 
128616.7%
 

KBA05_CCM2
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing8648
Missing (%)20.1%
Infinite0
Infinite (%)0.0%
Mean3.071049717
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:56:54.091041image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum9
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.176554058
Coefficient of variation (CV)0.3831113678
Kurtosis5.605164202
Mean3.071049717
Median Absolute Deviation (MAD)1
Skewness1.299056115
Sum105380
Variance1.384279451
MonotocityNot monotonic
2020-11-30T23:56:54.173147image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31443233.6%
 
4744517.3%
 
2725916.9%
 
124095.6%
 
523865.6%
 
93830.9%
 
(Missing)864820.1%
 
ValueCountFrequency (%) 
124095.6%
 
2725916.9%
 
31443233.6%
 
4744517.3%
 
523865.6%
 
93830.9%
 
ValueCountFrequency (%) 
93830.9%
 
523865.6%
 
4744517.3%
 
31443233.6%
 
2725916.9%
 
124095.6%
 

KBA05_CCM3
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing8648
Missing (%)20.1%
Infinite0
Infinite (%)0.0%
Mean3.120329895
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:56:54.261331image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum9
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.208367039
Coefficient of variation (CV)0.3872561812
Kurtosis4.689270463
Mean3.120329895
Median Absolute Deviation (MAD)1
Skewness1.13172801
Sum107071
Variance1.460150901
MonotocityNot monotonic
2020-11-30T23:56:54.344970image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31377032.1%
 
4787118.3%
 
2674015.7%
 
529506.9%
 
126006.1%
 
93830.9%
 
(Missing)864820.1%
 
ValueCountFrequency (%) 
126006.1%
 
2674015.7%
 
31377032.1%
 
4787118.3%
 
529506.9%
 
93830.9%
 
ValueCountFrequency (%) 
93830.9%
 
529506.9%
 
4787118.3%
 
31377032.1%
 
2674015.7%
 
126006.1%
 

KBA05_CCM4
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing8648
Missing (%)20.1%
Infinite0
Infinite (%)0.0%
Mean1.35317946
Minimum0
Maximum9
Zeros10887
Zeros (%)25.3%
Memory size335.8 KiB
2020-11-30T23:56:54.435866image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile4
Maximum9
Range9
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.439305462
Coefficient of variation (CV)1.063647139
Kurtosis7.038340461
Mean1.35317946
Median Absolute Deviation (MAD)1
Skewness1.965284843
Sum46433
Variance2.071600213
MonotocityNot monotonic
2020-11-30T23:56:54.508941image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
11100225.6%
 
01088725.3%
 
2625314.6%
 
336788.6%
 
421114.9%
 
93830.9%
 
(Missing)864820.1%
 
ValueCountFrequency (%) 
01088725.3%
 
11100225.6%
 
2625314.6%
 
336788.6%
 
421114.9%
 
93830.9%
 
ValueCountFrequency (%) 
93830.9%
 
421114.9%
 
336788.6%
 
2625314.6%
 
11100225.6%
 
01088725.3%
 

KBA05_DIESEL
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing8648
Missing (%)20.1%
Infinite0
Infinite (%)0.0%
Mean2.103456315
Minimum0
Maximum9
Zeros2354
Zeros (%)5.5%
Memory size335.8 KiB
2020-11-30T23:56:54.586365image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q33
95-th percentile4
Maximum9
Range9
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.249751295
Coefficient of variation (CV)0.5941417875
Kurtosis8.509008969
Mean2.103456315
Median Absolute Deviation (MAD)1
Skewness1.755831312
Sum72178
Variance1.561878299
MonotocityNot monotonic
2020-11-30T23:56:54.662805image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
21387632.3%
 
3760117.7%
 
1740817.2%
 
426926.3%
 
023545.5%
 
93830.9%
 
(Missing)864820.1%
 
ValueCountFrequency (%) 
023545.5%
 
1740817.2%
 
21387632.3%
 
3760117.7%
 
426926.3%
 
93830.9%
 
ValueCountFrequency (%) 
93830.9%
 
426926.3%
 
3760117.7%
 
21387632.3%
 
1740817.2%
 
023545.5%
 

KBA05_FRAU
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing8648
Missing (%)20.1%
Infinite0
Infinite (%)0.0%
Mean3.062481786
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:56:54.743395image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum9
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.200161724
Coefficient of variation (CV)0.3918918733
Kurtosis5.107672919
Mean3.062481786
Median Absolute Deviation (MAD)1
Skewness1.25596147
Sum105086
Variance1.440388163
MonotocityNot monotonic
2020-11-30T23:56:54.828384image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31434633.4%
 
2737117.2%
 
4681915.9%
 
527976.5%
 
125986.0%
 
93830.9%
 
(Missing)864820.1%
 
ValueCountFrequency (%) 
125986.0%
 
2737117.2%
 
31434633.4%
 
4681915.9%
 
527976.5%
 
93830.9%
 
ValueCountFrequency (%) 
93830.9%
 
527976.5%
 
4681915.9%
 
31434633.4%
 
2737117.2%
 
125986.0%
 

KBA05_GBZ
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing8648
Missing (%)20.1%
Infinite0
Infinite (%)0.0%
Mean3.397651105
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:56:54.928959image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median4
Q35
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.299036571
Coefficient of variation (CV)0.3823337155
Kurtosis-0.92052144
Mean3.397651105
Median Absolute Deviation (MAD)1
Skewness-0.3875388871
Sum116587
Variance1.687496013
MonotocityNot monotonic
2020-11-30T23:56:55.008740image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
4886720.6%
 
5859020.0%
 
3830519.3%
 
2470210.9%
 
138509.0%
 
(Missing)864820.1%
 
ValueCountFrequency (%) 
138509.0%
 
2470210.9%
 
3830519.3%
 
4886720.6%
 
5859020.0%
 
ValueCountFrequency (%) 
5859020.0%
 
4886720.6%
 
3830519.3%
 
2470210.9%
 
138509.0%
 

KBA05_HERST1
Real number (ℝ≥0)

MISSING
ZEROS

Distinct7
Distinct (%)< 0.1%
Missing8648
Missing (%)20.1%
Infinite0
Infinite (%)0.0%
Mean2.508305648
Minimum0
Maximum9
Zeros2645
Zeros (%)6.2%
Memory size335.8 KiB
2020-11-30T23:56:55.097087image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median2
Q33
95-th percentile5
Maximum9
Range9
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.503743983
Coefficient of variation (CV)0.5995058795
Kurtosis2.406982689
Mean2.508305648
Median Absolute Deviation (MAD)1
Skewness0.8829167479
Sum86070
Variance2.261245968
MonotocityNot monotonic
2020-11-30T23:56:55.170653image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
21023223.8%
 
3839119.5%
 
1553312.9%
 
441979.8%
 
529336.8%
 
026456.2%
 
93830.9%
 
(Missing)864820.1%
 
ValueCountFrequency (%) 
026456.2%
 
1553312.9%
 
21023223.8%
 
3839119.5%
 
441979.8%
 
529336.8%
 
93830.9%
 
ValueCountFrequency (%) 
93830.9%
 
529336.8%
 
441979.8%
 
3839119.5%
 
21023223.8%
 
1553312.9%
 
026456.2%
 

KBA05_HERST2
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing8648
Missing (%)20.1%
Infinite0
Infinite (%)0.0%
Mean3.088535292
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:56:55.247744image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum9
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.180464334
Coefficient of variation (CV)0.3822084655
Kurtosis5.414501318
Mean3.088535292
Median Absolute Deviation (MAD)1
Skewness1.321144196
Sum105980
Variance1.393496045
MonotocityNot monotonic
2020-11-30T23:56:55.332712image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31427833.2%
 
2765317.8%
 
4711916.6%
 
527596.4%
 
121224.9%
 
93830.9%
 
(Missing)864820.1%
 
ValueCountFrequency (%) 
121224.9%
 
2765317.8%
 
31427833.2%
 
4711916.6%
 
527596.4%
 
93830.9%
 
ValueCountFrequency (%) 
93830.9%
 
527596.4%
 
4711916.6%
 
31427833.2%
 
2765317.8%
 
121224.9%
 

KBA05_HERST3
Real number (ℝ≥0)

MISSING
ZEROS

Distinct7
Distinct (%)< 0.1%
Missing8648
Missing (%)20.1%
Infinite0
Infinite (%)0.0%
Mean2.939208486
Minimum0
Maximum9
Zeros600
Zeros (%)1.4%
Memory size335.8 KiB
2020-11-30T23:56:55.425035image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum9
Range9
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.258517322
Coefficient of variation (CV)0.4281823926
Kurtosis4.667198085
Mean2.939208486
Median Absolute Deviation (MAD)1
Skewness1.025855911
Sum100856
Variance1.58386585
MonotocityNot monotonic
2020-11-30T23:56:55.503206image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
31399032.6%
 
2768817.9%
 
4633814.8%
 
129666.9%
 
523495.5%
 
06001.4%
 
93830.9%
 
(Missing)864820.1%
 
ValueCountFrequency (%) 
06001.4%
 
129666.9%
 
2768817.9%
 
31399032.6%
 
4633814.8%
 
523495.5%
 
93830.9%
 
ValueCountFrequency (%) 
93830.9%
 
523495.5%
 
4633814.8%
 
31399032.6%
 
2768817.9%
 
129666.9%
 
06001.4%
 

KBA05_HERST4
Real number (ℝ≥0)

MISSING
ZEROS

Distinct7
Distinct (%)< 0.1%
Missing8648
Missing (%)20.1%
Infinite0
Infinite (%)0.0%
Mean2.888995745
Minimum0
Maximum9
Zeros1037
Zeros (%)2.4%
Memory size335.8 KiB
2020-11-30T23:56:55.585177image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum9
Range9
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.356748115
Coefficient of variation (CV)0.4696262074
Kurtosis3.240260139
Mean2.888995745
Median Absolute Deviation (MAD)1
Skewness0.7988984006
Sum99133
Variance1.840765447
MonotocityNot monotonic
2020-11-30T23:56:55.661119image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
31215228.3%
 
2785618.3%
 
4631214.7%
 
136508.5%
 
529246.8%
 
010372.4%
 
93830.9%
 
(Missing)864820.1%
 
ValueCountFrequency (%) 
010372.4%
 
136508.5%
 
2785618.3%
 
31215228.3%
 
4631214.7%
 
529246.8%
 
93830.9%
 
ValueCountFrequency (%) 
93830.9%
 
529246.8%
 
4631214.7%
 
31215228.3%
 
2785618.3%
 
136508.5%
 
010372.4%
 

KBA05_HERST5
Real number (ℝ≥0)

MISSING
ZEROS

Distinct7
Distinct (%)< 0.1%
Missing8648
Missing (%)20.1%
Infinite0
Infinite (%)0.0%
Mean2.872471877
Minimum0
Maximum9
Zeros1641
Zeros (%)3.8%
Memory size335.8 KiB
2020-11-30T23:56:55.742202image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum9
Range9
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.399151011
Coefficient of variation (CV)0.487089542
Kurtosis2.81747835
Mean2.872471877
Median Absolute Deviation (MAD)1
Skewness0.6308281944
Sum98566
Variance1.957623552
MonotocityNot monotonic
2020-11-30T23:56:55.817688image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
31130326.3%
 
2781218.2%
 
4711316.6%
 
132947.7%
 
527686.4%
 
016413.8%
 
93830.9%
 
(Missing)864820.1%
 
ValueCountFrequency (%) 
016413.8%
 
132947.7%
 
2781218.2%
 
31130326.3%
 
4711316.6%
 
527686.4%
 
93830.9%
 
ValueCountFrequency (%) 
93830.9%
 
527686.4%
 
4711316.6%
 
31130326.3%
 
2781218.2%
 
132947.7%
 
016413.8%
 

KBA05_HERSTTEMP
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing7777
Missing (%)18.1%
Infinite0
Infinite (%)0.0%
Mean2.674491971
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:56:55.897268image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q33
95-th percentile5
Maximum9
Range8
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.344833271
Coefficient of variation (CV)0.5028369073
Kurtosis4.747922392
Mean2.674491971
Median Absolute Deviation (MAD)1
Skewness1.3770299
Sum94102
Variance1.808576528
MonotocityNot monotonic
2020-11-30T23:56:55.980748image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31216728.3%
 
2811418.9%
 
1746117.4%
 
4521112.1%
 
517554.1%
 
94771.1%
 
(Missing)777718.1%
 
ValueCountFrequency (%) 
1746117.4%
 
2811418.9%
 
31216728.3%
 
4521112.1%
 
517554.1%
 
94771.1%
 
ValueCountFrequency (%) 
94771.1%
 
517554.1%
 
4521112.1%
 
31216728.3%
 
2811418.9%
 
1746117.4%
 

KBA05_KRSAQUOT
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing8648
Missing (%)20.1%
Infinite0
Infinite (%)0.0%
Mean3.285277146
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:56:56.072490image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median3
Q34
95-th percentile5
Maximum9
Range8
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.241441684
Coefficient of variation (CV)0.3778803519
Kurtosis3.530424036
Mean3.285277146
Median Absolute Deviation (MAD)1
Skewness0.8832428082
Sum112731
Variance1.541177455
MonotocityNot monotonic
2020-11-30T23:56:56.155043image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31357531.6%
 
4803218.7%
 
2514712.0%
 
5474011.0%
 
124375.7%
 
93830.9%
 
(Missing)864820.1%
 
ValueCountFrequency (%) 
124375.7%
 
2514712.0%
 
31357531.6%
 
4803218.7%
 
5474011.0%
 
93830.9%
 
ValueCountFrequency (%) 
93830.9%
 
5474011.0%
 
4803218.7%
 
31357531.6%
 
2514712.0%
 
124375.7%
 

KBA05_KRSHERST1
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing8648
Missing (%)20.1%
Infinite0
Infinite (%)0.0%
Mean3.066998893
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:56:56.243888image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum9
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.158735549
Coefficient of variation (CV)0.3778076189
Kurtosis6.029329833
Mean3.066998893
Median Absolute Deviation (MAD)1
Skewness1.36870094
Sum105241
Variance1.342668072
MonotocityNot monotonic
2020-11-30T23:56:56.326278image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31411232.8%
 
4787318.3%
 
2774018.0%
 
121365.0%
 
520704.8%
 
93830.9%
 
(Missing)864820.1%
 
ValueCountFrequency (%) 
121365.0%
 
2774018.0%
 
31411232.8%
 
4787318.3%
 
520704.8%
 
93830.9%
 
ValueCountFrequency (%) 
93830.9%
 
520704.8%
 
4787318.3%
 
31411232.8%
 
2774018.0%
 
121365.0%
 

KBA05_KRSHERST2
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing8648
Missing (%)20.1%
Infinite0
Infinite (%)0.0%
Mean3.065221193
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:56:56.414715image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum9
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.206869309
Coefficient of variation (CV)0.3937299246
Kurtosis4.950031455
Mean3.065221193
Median Absolute Deviation (MAD)1
Skewness1.204069901
Sum105180
Variance1.456533529
MonotocityNot monotonic
2020-11-30T23:56:56.497113image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31413432.9%
 
4715516.7%
 
2712916.6%
 
127786.5%
 
527356.4%
 
93830.9%
 
(Missing)864820.1%
 
ValueCountFrequency (%) 
127786.5%
 
2712916.6%
 
31413432.9%
 
4715516.7%
 
527356.4%
 
93830.9%
 
ValueCountFrequency (%) 
93830.9%
 
527356.4%
 
4715516.7%
 
31413432.9%
 
2712916.6%
 
127786.5%
 

KBA05_KRSHERST3
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing8648
Missing (%)20.1%
Infinite0
Infinite (%)0.0%
Mean3.078247945
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:56:56.585389image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum9
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.233392628
Coefficient of variation (CV)0.4006800782
Kurtosis4.351613266
Mean3.078247945
Median Absolute Deviation (MAD)1
Skewness1.154885203
Sum105627
Variance1.521257374
MonotocityNot monotonic
2020-11-30T23:56:56.667085image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31378432.1%
 
2738517.2%
 
4660415.4%
 
533717.8%
 
127876.5%
 
93830.9%
 
(Missing)864820.1%
 
ValueCountFrequency (%) 
127876.5%
 
2738517.2%
 
31378432.1%
 
4660415.4%
 
533717.8%
 
93830.9%
 
ValueCountFrequency (%) 
93830.9%
 
533717.8%
 
4660415.4%
 
31378432.1%
 
2738517.2%
 
127876.5%
 

KBA05_KRSKLEIN
Categorical

MISSING

Distinct4
Distinct (%)< 0.1%
Missing8648
Missing (%)20.1%
Memory size335.8 KiB
2
20925 
1
6807 
3
6199 
9
 
383
ValueCountFrequency (%) 
22092548.7%
 
1680715.8%
 
3619914.4%
 
93830.9%
 
(Missing)864820.1%
 
2020-11-30T23:56:56.771376image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters8
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
.3431426.6%
 
03431426.6%
 
22092516.2%
 
n1729613.4%
 
a86486.7%
 
168075.3%
 
361994.8%
 
93830.3%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number6862853.2%
 
Other Punctuation3431426.6%
 
Lowercase Letter2594420.1%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
03431450.0%
 
22092530.5%
 
168079.9%
 
361999.0%
 
93830.6%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
.34314100.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n1729666.7%
 
a864833.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Common10294279.9%
 
Latin2594420.1%
 

Most frequent Common characters

ValueCountFrequency (%) 
.3431433.3%
 
03431433.3%
 
22092520.3%
 
168076.6%
 
361996.0%
 
93830.4%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n1729666.7%
 
a864833.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII128886100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
.3431426.6%
 
03431426.6%
 
22092516.2%
 
n1729613.4%
 
a86486.7%
 
168075.3%
 
361994.8%
 
93830.3%
 

KBA05_KRSOBER
Categorical

MISSING

Distinct4
Distinct (%)< 0.1%
Missing8648
Missing (%)20.1%
Memory size335.8 KiB
2
22210 
3
5904 
1
5817 
9
 
383
ValueCountFrequency (%) 
22221051.7%
 
3590413.7%
 
1581713.5%
 
93830.9%
 
(Missing)864820.1%
 
2020-11-30T23:56:56.867651image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters8
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
.3431426.6%
 
03431426.6%
 
22221017.2%
 
n1729613.4%
 
a86486.7%
 
359044.6%
 
158174.5%
 
93830.3%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number6862853.2%
 
Other Punctuation3431426.6%
 
Lowercase Letter2594420.1%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
03431450.0%
 
22221032.4%
 
359048.6%
 
158178.5%
 
93830.6%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
.34314100.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n1729666.7%
 
a864833.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Common10294279.9%
 
Latin2594420.1%
 

Most frequent Common characters

ValueCountFrequency (%) 
.3431433.3%
 
03431433.3%
 
22221021.6%
 
359045.7%
 
158175.7%
 
93830.4%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n1729666.7%
 
a864833.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII128886100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
.3431426.6%
 
03431426.6%
 
22221017.2%
 
n1729613.4%
 
a86486.7%
 
359044.6%
 
158174.5%
 
93830.3%
 

KBA05_KRSVAN
Categorical

MISSING

Distinct4
Distinct (%)< 0.1%
Missing8648
Missing (%)20.1%
Memory size335.8 KiB
2
23642 
3
5571 
1
4718 
9
 
383
ValueCountFrequency (%) 
22364255.0%
 
3557113.0%
 
1471811.0%
 
93830.9%
 
(Missing)864820.1%
 
2020-11-30T23:56:56.963764image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters8
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
.3431426.6%
 
03431426.6%
 
22364218.3%
 
n1729613.4%
 
a86486.7%
 
355714.3%
 
147183.7%
 
93830.3%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number6862853.2%
 
Other Punctuation3431426.6%
 
Lowercase Letter2594420.1%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
03431450.0%
 
22364234.4%
 
355718.1%
 
147186.9%
 
93830.6%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
.34314100.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n1729666.7%
 
a864833.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Common10294279.9%
 
Latin2594420.1%
 

Most frequent Common characters

ValueCountFrequency (%) 
.3431433.3%
 
03431433.3%
 
22364223.0%
 
355715.4%
 
147184.6%
 
93830.4%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n1729666.7%
 
a864833.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII128886100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
.3431426.6%
 
03431426.6%
 
22364218.3%
 
n1729613.4%
 
a86486.7%
 
355714.3%
 
147183.7%
 
93830.3%
 

KBA05_KRSZUL
Categorical

MISSING

Distinct4
Distinct (%)< 0.1%
Missing8648
Missing (%)20.1%
Memory size335.8 KiB
2
18370 
1
7959 
3
7602 
9
 
383
ValueCountFrequency (%) 
21837042.8%
 
1795918.5%
 
3760217.7%
 
93830.9%
 
(Missing)864820.1%
 
2020-11-30T23:56:57.062406image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters8
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
.3431426.6%
 
03431426.6%
 
21837014.3%
 
n1729613.4%
 
a86486.7%
 
179596.2%
 
376025.9%
 
93830.3%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number6862853.2%
 
Other Punctuation3431426.6%
 
Lowercase Letter2594420.1%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
03431450.0%
 
21837026.8%
 
1795911.6%
 
3760211.1%
 
93830.6%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
.34314100.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n1729666.7%
 
a864833.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Common10294279.9%
 
Latin2594420.1%
 

Most frequent Common characters

ValueCountFrequency (%) 
.3431433.3%
 
03431433.3%
 
21837017.8%
 
179597.7%
 
376027.4%
 
93830.4%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n1729666.7%
 
a864833.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII128886100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
.3431426.6%
 
03431426.6%
 
21837014.3%
 
n1729613.4%
 
a86486.7%
 
179596.2%
 
376025.9%
 
93830.3%
 

KBA05_KW1
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing8648
Missing (%)20.1%
Infinite0
Infinite (%)0.0%
Mean2.949350119
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:56:57.151733image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum9
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.234019412
Coefficient of variation (CV)0.4184038387
Kurtosis4.812061078
Mean2.949350119
Median Absolute Deviation (MAD)1
Skewness1.208199952
Sum101204
Variance1.522803908
MonotocityNot monotonic
2020-11-30T23:56:57.232995image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31328330.9%
 
2790218.4%
 
4677815.8%
 
137128.6%
 
522565.3%
 
93830.9%
 
(Missing)864820.1%
 
ValueCountFrequency (%) 
137128.6%
 
2790218.4%
 
31328330.9%
 
4677815.8%
 
522565.3%
 
93830.9%
 
ValueCountFrequency (%) 
93830.9%
 
522565.3%
 
4677815.8%
 
31328330.9%
 
2790218.4%
 
137128.6%
 

KBA05_KW2
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing8648
Missing (%)20.1%
Infinite0
Infinite (%)0.0%
Mean3.133036079
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:56:57.319727image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum9
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.177704189
Coefficient of variation (CV)0.3758987
Kurtosis5.317248036
Mean3.133036079
Median Absolute Deviation (MAD)1
Skewness1.254119633
Sum107507
Variance1.386987157
MonotocityNot monotonic
2020-11-30T23:56:57.401199image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31467634.2%
 
4750717.5%
 
2669615.6%
 
528906.7%
 
121625.0%
 
93830.9%
 
(Missing)864820.1%
 
ValueCountFrequency (%) 
121625.0%
 
2669615.6%
 
31467634.2%
 
4750717.5%
 
528906.7%
 
93830.9%
 
ValueCountFrequency (%) 
93830.9%
 
528906.7%
 
4750717.5%
 
31467634.2%
 
2669615.6%
 
121625.0%
 

KBA05_KW3
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing8648
Missing (%)20.1%
Infinite0
Infinite (%)0.0%
Mean1.57341027
Minimum0
Maximum9
Zeros7676
Zeros (%)17.9%
Memory size335.8 KiB
2020-11-30T23:56:57.491842image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q32
95-th percentile4
Maximum9
Range9
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.4323919
Coefficient of variation (CV)0.9103740628
Kurtosis6.209303021
Mean1.57341027
Median Absolute Deviation (MAD)1
Skewness1.765938853
Sum53990
Variance2.051746555
MonotocityNot monotonic
2020-11-30T23:56:57.569089image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
11168527.2%
 
2773818.0%
 
0767617.9%
 
339469.2%
 
428866.7%
 
93830.9%
 
(Missing)864820.1%
 
ValueCountFrequency (%) 
0767617.9%
 
11168527.2%
 
2773818.0%
 
339469.2%
 
428866.7%
 
93830.9%
 
ValueCountFrequency (%) 
93830.9%
 
428866.7%
 
339469.2%
 
2773818.0%
 
11168527.2%
 
0767617.9%
 

KBA05_MAXAH
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing8648
Missing (%)20.1%
Infinite0
Infinite (%)0.0%
Mean3.65693303
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:56:57.650231image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median4
Q35
95-th percentile5
Maximum9
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.356138266
Coefficient of variation (CV)0.3708403339
Kurtosis0.9747647514
Mean3.65693303
Median Absolute Deviation (MAD)1
Skewness0.3895971997
Sum125484
Variance1.839110997
MonotocityNot monotonic
2020-11-30T23:56:57.731033image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
51196227.8%
 
3934521.8%
 
2632514.7%
 
4508111.8%
 
112182.8%
 
93830.9%
 
(Missing)864820.1%
 
ValueCountFrequency (%) 
112182.8%
 
2632514.7%
 
3934521.8%
 
4508111.8%
 
51196227.8%
 
93830.9%
 
ValueCountFrequency (%) 
93830.9%
 
51196227.8%
 
4508111.8%
 
3934521.8%
 
2632514.7%
 
112182.8%
 

KBA05_MAXBJ
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing8648
Missing (%)20.1%
Infinite0
Infinite (%)0.0%
Mean2.494841756
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:56:57.823067image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q34
95-th percentile4
Maximum9
Range8
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.37048405
Coefficient of variation (CV)0.5493270454
Kurtosis3.505528937
Mean2.494841756
Median Absolute Deviation (MAD)1
Skewness1.163688247
Sum85608
Variance1.878226532
MonotocityNot monotonic
2020-11-30T23:56:57.914019image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
11040224.2%
 
4949022.1%
 
2831819.4%
 
3572113.3%
 
93830.9%
 
(Missing)864820.1%
 
ValueCountFrequency (%) 
11040224.2%
 
2831819.4%
 
3572113.3%
 
4949022.1%
 
93830.9%
 
ValueCountFrequency (%) 
93830.9%
 
4949022.1%
 
3572113.3%
 
2831819.4%
 
11040224.2%
 

KBA05_MAXHERST
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing8648
Missing (%)20.1%
Infinite0
Infinite (%)0.0%
Mean2.775805794
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:56:58.003096image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q33
95-th percentile5
Maximum9
Range8
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.294420547
Coefficient of variation (CV)0.4663224459
Kurtosis4.281331029
Mean2.775805794
Median Absolute Deviation (MAD)1
Skewness1.416249411
Sum95249
Variance1.675524552
MonotocityNot monotonic
2020-11-30T23:56:58.086674image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
21290530.0%
 
3910921.2%
 
4504811.7%
 
139689.2%
 
529016.8%
 
93830.9%
 
(Missing)864820.1%
 
ValueCountFrequency (%) 
139689.2%
 
21290530.0%
 
3910921.2%
 
4504811.7%
 
529016.8%
 
93830.9%
 
ValueCountFrequency (%) 
93830.9%
 
529016.8%
 
4504811.7%
 
3910921.2%
 
21290530.0%
 
139689.2%
 

KBA05_MAXSEG
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing8648
Missing (%)20.1%
Infinite0
Infinite (%)0.0%
Mean2.232936994
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:56:58.175885image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q33
95-th percentile4
Maximum9
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.160069864
Coefficient of variation (CV)0.5195264657
Kurtosis10.79783288
Mean2.232936994
Median Absolute Deviation (MAD)1
Skewness2.298905638
Sum76621
Variance1.34576209
MonotocityNot monotonic
2020-11-30T23:56:58.253550image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
21424133.1%
 
1878620.5%
 
3771017.9%
 
431947.4%
 
93830.9%
 
(Missing)864820.1%
 
ValueCountFrequency (%) 
1878620.5%
 
21424133.1%
 
3771017.9%
 
431947.4%
 
93830.9%
 
ValueCountFrequency (%) 
93830.9%
 
431947.4%
 
3771017.9%
 
21424133.1%
 
1878620.5%
 

KBA05_MAXVORB
Categorical

MISSING

Distinct4
Distinct (%)< 0.1%
Missing8648
Missing (%)20.1%
Memory size335.8 KiB
2
15978 
1
9898 
3
8055 
9
 
383
ValueCountFrequency (%) 
21597837.2%
 
1989823.0%
 
3805518.7%
 
93830.9%
 
(Missing)864820.1%
 
2020-11-30T23:56:58.355561image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters8
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
.3431426.6%
 
03431426.6%
 
n1729613.4%
 
21597812.4%
 
198987.7%
 
a86486.7%
 
380556.2%
 
93830.3%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number6862853.2%
 
Other Punctuation3431426.6%
 
Lowercase Letter2594420.1%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
03431450.0%
 
21597823.3%
 
1989814.4%
 
3805511.7%
 
93830.6%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
.34314100.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n1729666.7%
 
a864833.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Common10294279.9%
 
Latin2594420.1%
 

Most frequent Common characters

ValueCountFrequency (%) 
.3431433.3%
 
03431433.3%
 
21597815.5%
 
198989.6%
 
380557.8%
 
93830.4%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n1729666.7%
 
a864833.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII128886100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
.3431426.6%
 
03431426.6%
 
n1729613.4%
 
21597812.4%
 
198987.7%
 
a86486.7%
 
380556.2%
 
93830.3%
 

KBA05_MOD1
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing8648
Missing (%)20.1%
Infinite0
Infinite (%)0.0%
Mean1.446231859
Minimum0
Maximum9
Zeros11398
Zeros (%)26.5%
Memory size335.8 KiB
2020-11-30T23:56:58.445001image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile4
Maximum9
Range9
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.469448114
Coefficient of variation (CV)1.016052928
Kurtosis5.841506039
Mean1.446231859
Median Absolute Deviation (MAD)1
Skewness1.682487668
Sum49626
Variance2.15927776
MonotocityNot monotonic
2020-11-30T23:56:58.522870image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
01139826.5%
 
2875520.4%
 
1741217.3%
 
342079.8%
 
421595.0%
 
93830.9%
 
(Missing)864820.1%
 
ValueCountFrequency (%) 
01139826.5%
 
1741217.3%
 
2875520.4%
 
342079.8%
 
421595.0%
 
93830.9%
 
ValueCountFrequency (%) 
93830.9%
 
421595.0%
 
342079.8%
 
2875520.4%
 
1741217.3%
 
01139826.5%
 

KBA05_MOD2
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing8648
Missing (%)20.1%
Infinite0
Infinite (%)0.0%
Mean3.066241184
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:56:58.603027image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum9
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.181370091
Coefficient of variation (CV)0.3852828333
Kurtosis5.5058198
Mean3.066241184
Median Absolute Deviation (MAD)1
Skewness1.277101221
Sum105215
Variance1.395635292
MonotocityNot monotonic
2020-11-30T23:56:58.684634image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31422733.1%
 
4757017.6%
 
2728517.0%
 
125025.8%
 
523475.5%
 
93830.9%
 
(Missing)864820.1%
 
ValueCountFrequency (%) 
125025.8%
 
2728517.0%
 
31422733.1%
 
4757017.6%
 
523475.5%
 
93830.9%
 
ValueCountFrequency (%) 
93830.9%
 
523475.5%
 
4757017.6%
 
31422733.1%
 
2728517.0%
 
125025.8%
 

KBA05_MOD3
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing8648
Missing (%)20.1%
Infinite0
Infinite (%)0.0%
Mean3.076382818
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:56:58.773368image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum9
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.202863338
Coefficient of variation (CV)0.3909992382
Kurtosis4.930894176
Mean3.076382818
Median Absolute Deviation (MAD)1
Skewness1.20675574
Sum105563
Variance1.44688021
MonotocityNot monotonic
2020-11-30T23:56:58.853713image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31310930.5%
 
4796618.5%
 
2777718.1%
 
525736.0%
 
125065.8%
 
93830.9%
 
(Missing)864820.1%
 
ValueCountFrequency (%) 
125065.8%
 
2777718.1%
 
31310930.5%
 
4796618.5%
 
525736.0%
 
93830.9%
 
ValueCountFrequency (%) 
93830.9%
 
525736.0%
 
4796618.5%
 
31310930.5%
 
2777718.1%
 
125065.8%
 

KBA05_MOD4
Real number (ℝ≥0)

MISSING
ZEROS

Distinct7
Distinct (%)< 0.1%
Missing8648
Missing (%)20.1%
Infinite0
Infinite (%)0.0%
Mean2.781080608
Minimum0
Maximum9
Zeros1672
Zeros (%)3.9%
Memory size335.8 KiB
2020-11-30T23:56:58.952523image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum9
Range9
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.45132989
Coefficient of variation (CV)0.5218582612
Kurtosis2.338874769
Mean2.781080608
Median Absolute Deviation (MAD)1
Skewness0.6805024773
Sum95430
Variance2.106358451
MonotocityNot monotonic
2020-11-30T23:56:59.027017image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
31071324.9%
 
2770717.9%
 
4599313.9%
 
1469310.9%
 
531537.3%
 
016723.9%
 
93830.9%
 
(Missing)864820.1%
 
ValueCountFrequency (%) 
016723.9%
 
1469310.9%
 
2770717.9%
 
31071324.9%
 
4599313.9%
 
531537.3%
 
93830.9%
 
ValueCountFrequency (%) 
93830.9%
 
531537.3%
 
4599313.9%
 
31071324.9%
 
2770717.9%
 
1469310.9%
 
016723.9%
 

KBA05_MOD8
Real number (ℝ≥0)

MISSING
ZEROS

Distinct5
Distinct (%)< 0.1%
Missing8648
Missing (%)20.1%
Infinite0
Infinite (%)0.0%
Mean1.368974762
Minimum0
Maximum9
Zeros8542
Zeros (%)19.9%
Memory size335.8 KiB
2020-11-30T23:56:59.105628image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q32
95-th percentile3
Maximum9
Range9
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.258427257
Coefficient of variation (CV)0.9192479594
Kurtosis12.78645045
Mean1.368974762
Median Absolute Deviation (MAD)1
Skewness2.446301079
Sum46975
Variance1.583639161
MonotocityNot monotonic
2020-11-30T23:56:59.182421image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
11115926.0%
 
21032124.0%
 
0854219.9%
 
339099.1%
 
93830.9%
 
(Missing)864820.1%
 
ValueCountFrequency (%) 
0854219.9%
 
11115926.0%
 
21032124.0%
 
339099.1%
 
93830.9%
 
ValueCountFrequency (%) 
93830.9%
 
339099.1%
 
21032124.0%
 
11115926.0%
 
0854219.9%
 

KBA05_MODTEMP
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing7777
Missing (%)18.1%
Infinite0
Infinite (%)0.0%
Mean2.917947989
Minimum1
Maximum6
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:56:59.261657image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum6
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.198852574
Coefficient of variation (CV)0.4108546755
Kurtosis-0.689624471
Mean2.917947989
Median Absolute Deviation (MAD)1
Skewness-0.2299547074
Sum102668
Variance1.437247494
MonotocityNot monotonic
2020-11-30T23:56:59.347533image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31243028.9%
 
41013923.6%
 
1682715.9%
 
237468.7%
 
517554.1%
 
62880.7%
 
(Missing)777718.1%
 
ValueCountFrequency (%) 
1682715.9%
 
237468.7%
 
31243028.9%
 
41013923.6%
 
517554.1%
 
62880.7%
 
ValueCountFrequency (%) 
62880.7%
 
517554.1%
 
41013923.6%
 
31243028.9%
 
237468.7%
 
1682715.9%
 

KBA05_MOTOR
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing8648
Missing (%)20.1%
Infinite0
Infinite (%)0.0%
Mean2.651920499
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:56:59.428068image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q33
95-th percentile4
Maximum9
Range8
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.135971128
Coefficient of variation (CV)0.4283579121
Kurtosis8.860366319
Mean2.651920499
Median Absolute Deviation (MAD)1
Skewness1.736880028
Sum90998
Variance1.290430404
MonotocityNot monotonic
2020-11-30T23:56:59.511368image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31368931.9%
 
21003923.4%
 
4540112.6%
 
1480211.2%
 
93830.9%
 
(Missing)864820.1%
 
ValueCountFrequency (%) 
1480211.2%
 
21003923.4%
 
31368931.9%
 
4540112.6%
 
93830.9%
 
ValueCountFrequency (%) 
93830.9%
 
4540112.6%
 
31368931.9%
 
21003923.4%
 
1480211.2%
 

KBA05_MOTRAD
Real number (ℝ≥0)

MISSING
ZEROS

Distinct5
Distinct (%)< 0.1%
Missing8648
Missing (%)20.1%
Infinite0
Infinite (%)0.0%
Mean1.195255581
Minimum0
Maximum9
Zeros8023
Zeros (%)18.7%
Memory size335.8 KiB
2020-11-30T23:56:59.602870image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q31
95-th percentile3
Maximum9
Range9
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.196145263
Coefficient of variation (CV)1.000744344
Kurtosis16.2101777
Mean1.195255581
Median Absolute Deviation (MAD)0
Skewness3.018518769
Sum41014
Variance1.430763489
MonotocityNot monotonic
2020-11-30T23:56:59.675971image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
11810942.2%
 
0802318.7%
 
341129.6%
 
237238.7%
 
93470.8%
 
(Missing)864820.1%
 
ValueCountFrequency (%) 
0802318.7%
 
11810942.2%
 
237238.7%
 
341129.6%
 
93470.8%
 
ValueCountFrequency (%) 
93470.8%
 
341129.6%
 
237238.7%
 
11810942.2%
 
0802318.7%
 

KBA05_SEG1
Real number (ℝ≥0)

MISSING
ZEROS

Distinct5
Distinct (%)< 0.1%
Missing8648
Missing (%)20.1%
Infinite0
Infinite (%)0.0%
Mean1.166462668
Minimum0
Maximum9
Zeros10321
Zeros (%)24.0%
Memory size335.8 KiB
2020-11-30T23:56:59.753656image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile3
Maximum9
Range9
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.223336141
Coefficient of variation (CV)1.048757216
Kurtosis16.40272081
Mean1.166462668
Median Absolute Deviation (MAD)1
Skewness2.968055008
Sum40026
Variance1.496551314
MonotocityNot monotonic
2020-11-30T23:56:59.824827image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
11289130.0%
 
01032124.0%
 
2846919.7%
 
322505.2%
 
93830.9%
 
(Missing)864820.1%
 
ValueCountFrequency (%) 
01032124.0%
 
11289130.0%
 
2846919.7%
 
322505.2%
 
93830.9%
 
ValueCountFrequency (%) 
93830.9%
 
322505.2%
 
2846919.7%
 
11289130.0%
 
01032124.0%
 

KBA05_SEG10
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing8648
Missing (%)20.1%
Infinite0
Infinite (%)0.0%
Mean2.001253133
Minimum0
Maximum9
Zeros3972
Zeros (%)9.2%
Memory size335.8 KiB
2020-11-30T23:56:59.901247image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q33
95-th percentile4
Maximum9
Range9
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.325463855
Coefficient of variation (CV)0.6623169421
Kurtosis6.840764292
Mean2.001253133
Median Absolute Deviation (MAD)1
Skewness1.522291599
Sum68671
Variance1.756854432
MonotocityNot monotonic
2020-11-30T23:56:59.978363image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
21280929.8%
 
1733517.1%
 
3698916.3%
 
039729.2%
 
428266.6%
 
93830.9%
 
(Missing)864820.1%
 
ValueCountFrequency (%) 
039729.2%
 
1733517.1%
 
21280929.8%
 
3698916.3%
 
428266.6%
 
93830.9%
 
ValueCountFrequency (%) 
93830.9%
 
428266.6%
 
3698916.3%
 
21280929.8%
 
1733517.1%
 
039729.2%
 

KBA05_SEG2
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing8648
Missing (%)20.1%
Infinite0
Infinite (%)0.0%
Mean3.028618057
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:00.058087image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum9
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.184516939
Coefficient of variation (CV)0.3911080622
Kurtosis5.61446224
Mean3.028618057
Median Absolute Deviation (MAD)1
Skewness1.28784234
Sum103924
Variance1.40308038
MonotocityNot monotonic
2020-11-30T23:57:00.139655image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31447533.7%
 
2725816.9%
 
4722216.8%
 
128086.5%
 
521685.0%
 
93830.9%
 
(Missing)864820.1%
 
ValueCountFrequency (%) 
128086.5%
 
2725816.9%
 
31447533.7%
 
4722216.8%
 
521685.0%
 
93830.9%
 
ValueCountFrequency (%) 
93830.9%
 
521685.0%
 
4722216.8%
 
31447533.7%
 
2725816.9%
 
128086.5%
 

KBA05_SEG3
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing8648
Missing (%)20.1%
Infinite0
Infinite (%)0.0%
Mean3.053709856
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:00.228790image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum9
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.208823446
Coefficient of variation (CV)0.3958540604
Kurtosis4.881259485
Mean3.053709856
Median Absolute Deviation (MAD)1
Skewness1.243400618
Sum104785
Variance1.461254123
MonotocityNot monotonic
2020-11-30T23:57:00.309569image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31287930.0%
 
2838219.5%
 
4753717.5%
 
526646.2%
 
124695.7%
 
93830.9%
 
(Missing)864820.1%
 
ValueCountFrequency (%) 
124695.7%
 
2838219.5%
 
31287930.0%
 
4753717.5%
 
526646.2%
 
93830.9%
 
ValueCountFrequency (%) 
93830.9%
 
526646.2%
 
4753717.5%
 
31287930.0%
 
2838219.5%
 
124695.7%
 

KBA05_SEG4
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing8648
Missing (%)20.1%
Infinite0
Infinite (%)0.0%
Mean3.082765052
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:00.397181image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum9
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.166556021
Coefficient of variation (CV)0.3784122374
Kurtosis5.848310393
Mean3.082765052
Median Absolute Deviation (MAD)1
Skewness1.341649132
Sum105782
Variance1.360852949
MonotocityNot monotonic
2020-11-30T23:57:00.480262image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31548636.0%
 
4680715.8%
 
2673915.7%
 
525686.0%
 
123315.4%
 
93830.9%
 
(Missing)864820.1%
 
ValueCountFrequency (%) 
123315.4%
 
2673915.7%
 
31548636.0%
 
4680715.8%
 
525686.0%
 
93830.9%
 
ValueCountFrequency (%) 
93830.9%
 
525686.0%
 
4680715.8%
 
31548636.0%
 
2673915.7%
 
123315.4%
 

KBA05_SEG5
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing8648
Missing (%)20.1%
Infinite0
Infinite (%)0.0%
Mean1.585941598
Minimum0
Maximum9
Zeros7092
Zeros (%)16.5%
Memory size335.8 KiB
2020-11-30T23:57:00.572810image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q32
95-th percentile4
Maximum9
Range9
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.390973669
Coefficient of variation (CV)0.8770648745
Kurtosis7.119229204
Mean1.585941598
Median Absolute Deviation (MAD)1
Skewness1.849411219
Sum54420
Variance1.934807747
MonotocityNot monotonic
2020-11-30T23:57:00.649317image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
11159727.0%
 
2867420.2%
 
0709216.5%
 
342449.9%
 
423245.4%
 
93830.9%
 
(Missing)864820.1%
 
ValueCountFrequency (%) 
0709216.5%
 
11159727.0%
 
2867420.2%
 
342449.9%
 
423245.4%
 
93830.9%
 
ValueCountFrequency (%) 
93830.9%
 
423245.4%
 
342449.9%
 
2867420.2%
 
11159727.0%
 
0709216.5%
 

KBA05_SEG6
Categorical

MISSING

Distinct3
Distinct (%)< 0.1%
Missing8648
Missing (%)20.1%
Memory size335.8 KiB
0
29474 
1
4457 
9
 
383
ValueCountFrequency (%) 
02947468.6%
 
1445710.4%
 
93830.9%
 
(Missing)864820.1%
 
2020-11-30T23:57:00.746655image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters6
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
06378849.5%
 
.3431426.6%
 
n1729613.4%
 
a86486.7%
 
144573.5%
 
93830.3%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number6862853.2%
 
Other Punctuation3431426.6%
 
Lowercase Letter2594420.1%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
06378892.9%
 
144576.5%
 
93830.6%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
.34314100.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n1729666.7%
 
a864833.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Common10294279.9%
 
Latin2594420.1%
 

Most frequent Common characters

ValueCountFrequency (%) 
06378862.0%
 
.3431433.3%
 
144574.3%
 
93830.4%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n1729666.7%
 
a864833.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII128886100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
06378849.5%
 
.3431426.6%
 
n1729613.4%
 
a86486.7%
 
144573.5%
 
93830.3%
 

KBA05_SEG7
Real number (ℝ≥0)

MISSING
ZEROS

Distinct5
Distinct (%)< 0.1%
Missing8648
Missing (%)20.1%
Infinite0
Infinite (%)0.0%
Mean0.9753744827
Minimum0
Maximum9
Zeros15246
Zeros (%)35.5%
Memory size335.8 KiB
2020-11-30T23:57:00.834271image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile3
Maximum9
Range9
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.273079894
Coefficient of variation (CV)1.305221653
Kurtosis15.28259537
Mean0.9753744827
Median Absolute Deviation (MAD)1
Skewness2.965054422
Sum33469
Variance1.620732417
MonotocityNot monotonic
2020-11-30T23:57:00.910270image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
01524635.5%
 
1961722.4%
 
2679915.8%
 
322695.3%
 
93830.9%
 
(Missing)864820.1%
 
ValueCountFrequency (%) 
01524635.5%
 
1961722.4%
 
2679915.8%
 
322695.3%
 
93830.9%
 
ValueCountFrequency (%) 
93830.9%
 
322695.3%
 
2679915.8%
 
1961722.4%
 
01524635.5%
 

KBA05_SEG8
Real number (ℝ≥0)

MISSING
ZEROS

Distinct5
Distinct (%)< 0.1%
Missing8648
Missing (%)20.1%
Infinite0
Infinite (%)0.0%
Mean0.8608148278
Minimum0
Maximum9
Zeros17259
Zeros (%)40.2%
Memory size335.8 KiB
2020-11-30T23:57:00.990700image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile3
Maximum9
Range9
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.258170646
Coefficient of variation (CV)1.46160429
Kurtosis17.23364985
Mean0.8608148278
Median Absolute Deviation (MAD)0
Skewness3.254561687
Sum29538
Variance1.582993373
MonotocityNot monotonic
2020-11-30T23:57:01.063027image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
01725940.2%
 
1914921.3%
 
2562713.1%
 
318964.4%
 
93830.9%
 
(Missing)864820.1%
 
ValueCountFrequency (%) 
01725940.2%
 
1914921.3%
 
2562713.1%
 
318964.4%
 
93830.9%
 
ValueCountFrequency (%) 
93830.9%
 
318964.4%
 
2562713.1%
 
1914921.3%
 
01725940.2%
 

KBA05_SEG9
Real number (ℝ≥0)

MISSING
ZEROS

Distinct5
Distinct (%)< 0.1%
Missing8648
Missing (%)20.1%
Infinite0
Infinite (%)0.0%
Mean1.188523635
Minimum0
Maximum9
Zeros10318
Zeros (%)24.0%
Memory size335.8 KiB
2020-11-30T23:57:01.145459image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile3
Maximum9
Range9
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.232997213
Coefficient of variation (CV)1.037419178
Kurtosis15.62087495
Mean1.188523635
Median Absolute Deviation (MAD)1
Skewness2.864972318
Sum40783
Variance1.520282127
MonotocityNot monotonic
2020-11-30T23:57:01.220434image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
11230628.6%
 
01031824.0%
 
2889120.7%
 
324165.6%
 
93830.9%
 
(Missing)864820.1%
 
ValueCountFrequency (%) 
01031824.0%
 
11230628.6%
 
2889120.7%
 
324165.6%
 
93830.9%
 
ValueCountFrequency (%) 
93830.9%
 
324165.6%
 
2889120.7%
 
11230628.6%
 
01031824.0%
 

KBA05_VORB0
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing8648
Missing (%)20.1%
Infinite0
Infinite (%)0.0%
Mean3.142536574
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:01.300947image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum9
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.24960115
Coefficient of variation (CV)0.397640925
Kurtosis3.771401199
Mean3.142536574
Median Absolute Deviation (MAD)1
Skewness0.9708559709
Sum107833
Variance1.561503034
MonotocityNot monotonic
2020-11-30T23:57:01.380951image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31174227.3%
 
4889320.7%
 
2719616.7%
 
532747.6%
 
128266.6%
 
93830.9%
 
(Missing)864820.1%
 
ValueCountFrequency (%) 
128266.6%
 
2719616.7%
 
31174227.3%
 
4889320.7%
 
532747.6%
 
93830.9%
 
ValueCountFrequency (%) 
93830.9%
 
532747.6%
 
4889320.7%
 
31174227.3%
 
2719616.7%
 
128266.6%
 

KBA05_VORB1
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing8648
Missing (%)20.1%
Infinite0
Infinite (%)0.0%
Mean3.066153756
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:01.468040image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum9
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.190798015
Coefficient of variation (CV)0.3883686564
Kurtosis5.321383657
Mean3.066153756
Median Absolute Deviation (MAD)1
Skewness1.269399122
Sum105212
Variance1.417999912
MonotocityNot monotonic
2020-11-30T23:57:01.551547image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31476234.4%
 
2704216.4%
 
4684415.9%
 
526846.2%
 
125996.0%
 
93830.9%
 
(Missing)864820.1%
 
ValueCountFrequency (%) 
125996.0%
 
2704216.4%
 
31476234.4%
 
4684415.9%
 
526846.2%
 
93830.9%
 
ValueCountFrequency (%) 
93830.9%
 
526846.2%
 
4684415.9%
 
31476234.4%
 
2704216.4%
 
125996.0%
 

KBA05_VORB2
Real number (ℝ≥0)

MISSING
ZEROS

Distinct7
Distinct (%)< 0.1%
Missing8648
Missing (%)20.1%
Infinite0
Infinite (%)0.0%
Mean2.526024363
Minimum0
Maximum9
Zeros2781
Zeros (%)6.5%
Memory size335.8 KiB
2020-11-30T23:57:01.643061image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median3
Q33
95-th percentile5
Maximum9
Range9
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.450604629
Coefficient of variation (CV)0.5742639104
Kurtosis2.989646207
Mean2.526024363
Median Absolute Deviation (MAD)1
Skewness0.8214422007
Sum86678
Variance2.104253788
MonotocityNot monotonic
2020-11-30T23:57:01.716740image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
31083925.2%
 
2884920.6%
 
1494011.5%
 
4453410.6%
 
027816.5%
 
519884.6%
 
93830.9%
 
(Missing)864820.1%
 
ValueCountFrequency (%) 
027816.5%
 
1494011.5%
 
2884920.6%
 
31083925.2%
 
4453410.6%
 
519884.6%
 
93830.9%
 
ValueCountFrequency (%) 
93830.9%
 
519884.6%
 
4453410.6%
 
31083925.2%
 
2884920.6%
 
1494011.5%
 
027816.5%
 

KBA05_ZUL1
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing8648
Missing (%)20.1%
Infinite0
Infinite (%)0.0%
Mean2.920557207
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:01.793778image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q33
95-th percentile5
Maximum9
Range8
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.180197785
Coefficient of variation (CV)0.4041002116
Kurtosis6.205794046
Mean2.920557207
Median Absolute Deviation (MAD)1
Skewness1.396424703
Sum100216
Variance1.392866813
MonotocityNot monotonic
2020-11-30T23:57:01.876196image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31444233.6%
 
2807618.8%
 
4650215.1%
 
133187.7%
 
515933.7%
 
93830.9%
 
(Missing)864820.1%
 
ValueCountFrequency (%) 
133187.7%
 
2807618.8%
 
31444233.6%
 
4650215.1%
 
515933.7%
 
93830.9%
 
ValueCountFrequency (%) 
93830.9%
 
515933.7%
 
4650215.1%
 
31444233.6%
 
2807618.8%
 
133187.7%
 

KBA05_ZUL2
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing8648
Missing (%)20.1%
Infinite0
Infinite (%)0.0%
Mean3.109459696
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:01.970496image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum9
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.185905892
Coefficient of variation (CV)0.3813864814
Kurtosis5.191812642
Mean3.109459696
Median Absolute Deviation (MAD)1
Skewness1.248697912
Sum106698
Variance1.406372785
MonotocityNot monotonic
2020-11-30T23:57:02.052925image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31389832.3%
 
4774418.0%
 
2734017.1%
 
527386.4%
 
122115.1%
 
93830.9%
 
(Missing)864820.1%
 
ValueCountFrequency (%) 
122115.1%
 
2734017.1%
 
31389832.3%
 
4774418.0%
 
527386.4%
 
93830.9%
 
ValueCountFrequency (%) 
93830.9%
 
527386.4%
 
4774418.0%
 
31389832.3%
 
2734017.1%
 
122115.1%
 

KBA05_ZUL3
Real number (ℝ≥0)

MISSING
ZEROS

Distinct7
Distinct (%)< 0.1%
Missing8648
Missing (%)20.1%
Infinite0
Infinite (%)0.0%
Mean2.857783995
Minimum0
Maximum9
Zeros2023
Zeros (%)4.7%
Memory size335.8 KiB
2020-11-30T23:57:02.149232image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median3
Q34
95-th percentile5
Maximum9
Range9
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.423313285
Coefficient of variation (CV)0.4980478886
Kurtosis2.605736653
Mean2.857783995
Median Absolute Deviation (MAD)1
Skewness0.5349743533
Sum98062
Variance2.025820706
MonotocityNot monotonic
2020-11-30T23:57:02.229703image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
31099525.6%
 
4765717.8%
 
2749017.4%
 
132027.5%
 
525646.0%
 
020234.7%
 
93830.9%
 
(Missing)864820.1%
 
ValueCountFrequency (%) 
020234.7%
 
132027.5%
 
2749017.4%
 
31099525.6%
 
4765717.8%
 
525646.0%
 
93830.9%
 
ValueCountFrequency (%) 
93830.9%
 
525646.0%
 
4765717.8%
 
31099525.6%
 
2749017.4%
 
132027.5%
 
020234.7%
 

KBA05_ZUL4
Real number (ℝ≥0)

MISSING
ZEROS

Distinct7
Distinct (%)< 0.1%
Missing8648
Missing (%)20.1%
Infinite0
Infinite (%)0.0%
Mean2.342833829
Minimum0
Maximum9
Zeros3181
Zeros (%)7.4%
Memory size335.8 KiB
2020-11-30T23:57:02.309899image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q33
95-th percentile5
Maximum9
Range9
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.567759636
Coefficient of variation (CV)0.6691723575
Kurtosis2.004025628
Mean2.342833829
Median Absolute Deviation (MAD)1
Skewness0.9298431483
Sum80392
Variance2.457870278
MonotocityNot monotonic
2020-11-30T23:57:02.383752image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
2889420.7%
 
1822419.1%
 
3605114.1%
 
4512511.9%
 
031817.4%
 
524565.7%
 
93830.9%
 
(Missing)864820.1%
 
ValueCountFrequency (%) 
031817.4%
 
1822419.1%
 
2889420.7%
 
3605114.1%
 
4512511.9%
 
524565.7%
 
93830.9%
 
ValueCountFrequency (%) 
93830.9%
 
524565.7%
 
4512511.9%
 
3605114.1%
 
2889420.7%
 
1822419.1%
 
031817.4%
 

KBA13_ALTERHALTER_30
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean2.900314286
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:02.462451image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.063798158
Coefficient of variation (CV)0.3667872006
Kurtosis-0.3936613809
Mean2.900314286
Median Absolute Deviation (MAD)1
Skewness0.03494963749
Sum101511
Variance1.13166652
MonotocityNot monotonic
2020-11-30T23:57:02.548647image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31470434.2%
 
2746317.4%
 
4628014.6%
 
138539.0%
 
527006.3%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
138539.0%
 
2746317.4%
 
31470434.2%
 
4628014.6%
 
527006.3%
 
ValueCountFrequency (%) 
527006.3%
 
4628014.6%
 
31470434.2%
 
2746317.4%
 
138539.0%
 

KBA13_ALTERHALTER_45
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean3.001771429
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:02.639758image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.100274002
Coefficient of variation (CV)0.3665415666
Kurtosis-0.5274508514
Mean3.001771429
Median Absolute Deviation (MAD)1
Skewness-0.009034826677
Sum105062
Variance1.210602879
MonotocityNot monotonic
2020-11-30T23:57:02.723995image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31374132.0%
 
4718516.7%
 
2703716.4%
 
135408.2%
 
534978.1%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
135408.2%
 
2703716.4%
 
31374132.0%
 
4718516.7%
 
534978.1%
 
ValueCountFrequency (%) 
534978.1%
 
4718516.7%
 
31374132.0%
 
2703716.4%
 
135408.2%
 

KBA13_ALTERHALTER_60
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean2.899114286
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:02.815946image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.065804974
Coefficient of variation (CV)0.367631238
Kurtosis-0.4368066109
Mean2.899114286
Median Absolute Deviation (MAD)1
Skewness0.08254813528
Sum101469
Variance1.135940242
MonotocityNot monotonic
2020-11-30T23:57:02.904528image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31405132.7%
 
2820619.1%
 
4635514.8%
 
136148.4%
 
527746.5%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
136148.4%
 
2820619.1%
 
31405132.7%
 
4635514.8%
 
527746.5%
 
ValueCountFrequency (%) 
527746.5%
 
4635514.8%
 
31405132.7%
 
2820619.1%
 
136148.4%
 

KBA13_ALTERHALTER_61
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean3.150714286
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:02.996759image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.092247684
Coefficient of variation (CV)0.3466666874
Kurtosis-0.5234357867
Mean3.150714286
Median Absolute Deviation (MAD)1
Skewness-0.06095169605
Sum110275
Variance1.193005004
MonotocityNot monotonic
2020-11-30T23:57:03.080552image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31366131.8%
 
4794818.5%
 
2632114.7%
 
5444710.4%
 
126236.1%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
126236.1%
 
2632114.7%
 
31366131.8%
 
4794818.5%
 
5444710.4%
 
ValueCountFrequency (%) 
5444710.4%
 
4794818.5%
 
31366131.8%
 
2632114.7%
 
126236.1%
 

KBA13_ANTG1
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean2.274971429
Minimum0
Maximum4
Zeros340
Zeros (%)0.8%
Memory size335.8 KiB
2020-11-30T23:57:03.171368image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median2
Q33
95-th percentile4
Maximum4
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9261060205
Coefficient of variation (CV)0.407084682
Kurtosis-0.6638896824
Mean2.274971429
Median Absolute Deviation (MAD)1
Skewness0.05605905125
Sum79624
Variance0.8576723613
MonotocityNot monotonic
2020-11-30T23:57:03.254434image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
21308830.5%
 
31107225.8%
 
1725616.9%
 
432447.6%
 
03400.8%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
03400.8%
 
1725616.9%
 
21308830.5%
 
31107225.8%
 
432447.6%
 
ValueCountFrequency (%) 
432447.6%
 
31107225.8%
 
21308830.5%
 
1725616.9%
 
03400.8%
 

KBA13_ANTG2
Real number (ℝ≥0)

MISSING
ZEROS

Distinct5
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean2.694314286
Minimum0
Maximum4
Zeros489
Zeros (%)1.1%
Memory size335.8 KiB
2020-11-30T23:57:03.344432image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median3
Q33
95-th percentile4
Maximum4
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9260257026
Coefficient of variation (CV)0.3436962449
Kurtosis-0.1671938302
Mean2.694314286
Median Absolute Deviation (MAD)1
Skewness-0.4336013116
Sum94301
Variance0.8575236019
MonotocityNot monotonic
2020-11-30T23:57:03.428378image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31469834.2%
 
2998823.2%
 
4680215.8%
 
130237.0%
 
04891.1%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
04891.1%
 
130237.0%
 
2998823.2%
 
31469834.2%
 
4680215.8%
 
ValueCountFrequency (%) 
4680215.8%
 
31469834.2%
 
2998823.2%
 
130237.0%
 
04891.1%
 

KBA13_ANTG3
Categorical

MISSING

Distinct4
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Memory size335.8 KiB
1
10716 
2
10442 
0
7120 
3
6722 
ValueCountFrequency (%) 
11071624.9%
 
21044224.3%
 
0712016.6%
 
3672215.6%
 
(Missing)796218.5%
 
2020-11-30T23:57:03.538840image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters7
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
04212032.7%
 
.3500027.2%
 
n1592412.4%
 
1107168.3%
 
2104428.1%
 
a79626.2%
 
367225.2%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number7000054.3%
 
Other Punctuation3500027.2%
 
Lowercase Letter2388618.5%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
04212060.2%
 
11071615.3%
 
21044214.9%
 
367229.6%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
.35000100.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n1592466.7%
 
a796233.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Common10500081.5%
 
Latin2388618.5%
 

Most frequent Common characters

ValueCountFrequency (%) 
04212040.1%
 
.3500033.3%
 
11071610.2%
 
2104429.9%
 
367226.4%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n1592466.7%
 
a796233.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII128886100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
04212032.7%
 
.3500027.2%
 
n1592412.4%
 
1107168.3%
 
2104428.1%
 
a79626.2%
 
367225.2%
 

KBA13_ANTG4
Categorical

MISSING

Distinct3
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Memory size335.8 KiB
0
18785 
1
11393 
2
4822 
ValueCountFrequency (%) 
01878543.7%
 
11139326.5%
 
2482211.2%
 
(Missing)796218.5%
 
2020-11-30T23:57:03.642668image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters6
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
05378541.7%
 
.3500027.2%
 
n1592412.4%
 
1113938.8%
 
a79626.2%
 
248223.7%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number7000054.3%
 
Other Punctuation3500027.2%
 
Lowercase Letter2388618.5%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
05378576.8%
 
11139316.3%
 
248226.9%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
.35000100.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n1592466.7%
 
a796233.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Common10500081.5%
 
Latin2388618.5%
 

Most frequent Common characters

ValueCountFrequency (%) 
05378551.2%
 
.3500033.3%
 
11139310.9%
 
248224.6%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n1592466.7%
 
a796233.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII128886100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
05378541.7%
 
.3500027.2%
 
n1592412.4%
 
1113938.8%
 
a79626.2%
 
248223.7%
 

KBA13_ANZAHL_PKW
Real number (ℝ≥0)

MISSING

Distinct1230
Distinct (%)3.5%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean620.8817143
Minimum0
Maximum2300
Zeros4
Zeros (%)< 0.1%
Memory size335.8 KiB
2020-11-30T23:57:03.745597image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile206
Q1389
median549
Q3773
95-th percentile1300
Maximum2300
Range2300
Interquartile range (IQR)384

Descriptive statistics

Standard deviation338.5713782
Coefficient of variation (CV)0.5453073756
Kurtosis2.203107266
Mean620.8817143
Median Absolute Deviation (MAD)183.5
Skewness1.31044492
Sum21730860
Variance114630.5781
MonotocityNot monotonic
2020-11-30T23:57:03.868504image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
14004941.1%
 
15003820.9%
 
13002950.7%
 
16002820.7%
 
17001540.4%
 
18001350.3%
 
1900880.2%
 
517850.2%
 
534820.2%
 
377780.2%
 
454770.2%
 
420760.2%
 
364740.2%
 
396730.2%
 
457720.2%
 
455710.2%
 
410710.2%
 
408710.2%
 
518700.2%
 
402700.2%
 
509690.2%
 
543690.2%
 
412690.2%
 
491690.2%
 
489680.2%
 
Other values (1205)3185674.1%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
04< 0.1%
 
21< 0.1%
 
41< 0.1%
 
151< 0.1%
 
252< 0.1%
 
261< 0.1%
 
272< 0.1%
 
312< 0.1%
 
321< 0.1%
 
331< 0.1%
 
ValueCountFrequency (%) 
2300250.1%
 
220015< 0.1%
 
2100240.1%
 
2000530.1%
 
1900880.2%
 
18001350.3%
 
17001540.4%
 
16002820.7%
 
15003820.9%
 
14004941.1%
 

KBA13_AUDI
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean3.104914286
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:03.971981image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.0125185
Coefficient of variation (CV)0.3261019167
Kurtosis-0.2783339514
Mean3.104914286
Median Absolute Deviation (MAD)1
Skewness-0.02360802934
Sum108672
Variance1.025193712
MonotocityNot monotonic
2020-11-30T23:57:04.064034image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31519835.4%
 
4785918.3%
 
2645515.0%
 
533117.7%
 
121775.1%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
121775.1%
 
2645515.0%
 
31519835.4%
 
4785918.3%
 
533117.7%
 
ValueCountFrequency (%) 
533117.7%
 
4785918.3%
 
31519835.4%
 
2645515.0%
 
121775.1%
 

KBA13_AUTOQUOTE
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean2.913028571
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:04.155097image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.046140572
Coefficient of variation (CV)0.3591247207
Kurtosis-0.3779847982
Mean2.913028571
Median Absolute Deviation (MAD)1
Skewness0.04030348728
Sum101956
Variance1.094410097
MonotocityNot monotonic
2020-11-30T23:57:04.239127image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31456133.9%
 
2782718.2%
 
4656915.3%
 
134688.1%
 
525756.0%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
134688.1%
 
2782718.2%
 
31456133.9%
 
4656915.3%
 
525756.0%
 
ValueCountFrequency (%) 
525756.0%
 
4656915.3%
 
31456133.9%
 
2782718.2%
 
134688.1%
 

KBA13_BAUMAX
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean1.8578
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:04.331277image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q32
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.42125991
Coefficient of variation (CV)0.765023097
Kurtosis0.2477721446
Mean1.8578
Median Absolute Deviation (MAD)0
Skewness1.363037581
Sum65023
Variance2.019979731
MonotocityNot monotonic
2020-11-30T23:57:04.411018image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
12373555.2%
 
541559.7%
 
228086.5%
 
323115.4%
 
419914.6%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
12373555.2%
 
228086.5%
 
323115.4%
 
419914.6%
 
541559.7%
 
ValueCountFrequency (%) 
541559.7%
 
419914.6%
 
323115.4%
 
228086.5%
 
12373555.2%
 

KBA13_BJ_1999
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean2.902085714
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:04.498387image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q33
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9653182981
Coefficient of variation (CV)0.3326291478
Kurtosis-0.1566269553
Mean2.902085714
Median Absolute Deviation (MAD)1
Skewness0.04402153997
Sum101573
Variance0.9318394166
MonotocityNot monotonic
2020-11-30T23:57:04.585306image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31574936.7%
 
2825619.2%
 
4642915.0%
 
126836.2%
 
518834.4%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
126836.2%
 
2825619.2%
 
31574936.7%
 
4642915.0%
 
518834.4%
 
ValueCountFrequency (%) 
518834.4%
 
4642915.0%
 
31574936.7%
 
2825619.2%
 
126836.2%
 

KBA13_BJ_2000
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean2.841171429
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:04.680097image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q33
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9802482609
Coefficient of variation (CV)0.3450155281
Kurtosis-0.1941031164
Mean2.841171429
Median Absolute Deviation (MAD)1
Skewness0.04488186942
Sum99441
Variance0.9608866531
MonotocityNot monotonic
2020-11-30T23:57:04.766995image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31556836.2%
 
2846119.7%
 
4594413.8%
 
132747.6%
 
517534.1%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
132747.6%
 
2846119.7%
 
31556836.2%
 
4594413.8%
 
517534.1%
 
ValueCountFrequency (%) 
517534.1%
 
4594413.8%
 
31556836.2%
 
2846119.7%
 
132747.6%
 

KBA13_BJ_2004
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean3.040314286
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:04.860474image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation0.9547629192
Coefficient of variation (CV)0.3140342838
Kurtosis-0.1114768658
Mean3.040314286
Median Absolute Deviation (MAD)1
Skewness0.01589447319
Sum106411
Variance0.9115722319
MonotocityNot monotonic
2020-11-30T23:57:04.946726image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31614637.6%
 
4745917.4%
 
2702616.4%
 
524295.7%
 
119404.5%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
119404.5%
 
2702616.4%
 
31614637.6%
 
4745917.4%
 
524295.7%
 
ValueCountFrequency (%) 
524295.7%
 
4745917.4%
 
31614637.6%
 
2702616.4%
 
119404.5%
 

KBA13_BJ_2006
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean3.080914286
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:05.047928image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9521368045
Coefficient of variation (CV)0.3090435878
Kurtosis-0.1264216365
Mean3.080914286
Median Absolute Deviation (MAD)1
Skewness-0.01385350498
Sum107832
Variance0.9065644945
MonotocityNot monotonic
2020-11-30T23:57:05.133586image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31599337.2%
 
4801618.7%
 
2667415.5%
 
525315.9%
 
117864.2%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
117864.2%
 
2667415.5%
 
31599337.2%
 
4801618.7%
 
525315.9%
 
ValueCountFrequency (%) 
525315.9%
 
4801618.7%
 
31599337.2%
 
2667415.5%
 
117864.2%
 

KBA13_BJ_2008
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean2.5298
Minimum0
Maximum5
Zeros5588
Zeros (%)13.0%
Memory size335.8 KiB
2020-11-30T23:57:05.223490image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median3
Q33
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.480473963
Coefficient of variation (CV)0.5852138362
Kurtosis-0.6424726231
Mean2.5298
Median Absolute Deviation (MAD)1
Skewness-0.2665339188
Sum88543
Variance2.191803154
MonotocityNot monotonic
2020-11-30T23:57:05.307119image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31274829.7%
 
2667215.5%
 
0558813.0%
 
441619.7%
 
536208.4%
 
122115.1%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
0558813.0%
 
122115.1%
 
2667215.5%
 
31274829.7%
 
441619.7%
 
536208.4%
 
ValueCountFrequency (%) 
536208.4%
 
441619.7%
 
31274829.7%
 
2667215.5%
 
122115.1%
 
0558813.0%
 

KBA13_BJ_2009
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean2.561742857
Minimum0
Maximum5
Zeros4183
Zeros (%)9.7%
Memory size335.8 KiB
2020-11-30T23:57:05.385167image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median3
Q33
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.460417812
Coefficient of variation (CV)0.5700875902
Kurtosis-0.7233699208
Mean2.561742857
Median Absolute Deviation (MAD)1
Skewness-0.1866605002
Sum89661
Variance2.132820186
MonotocityNot monotonic
2020-11-30T23:57:05.468394image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31281429.8%
 
2515912.0%
 
1476211.1%
 
442719.9%
 
041839.7%
 
538118.9%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
041839.7%
 
1476211.1%
 
2515912.0%
 
31281429.8%
 
442719.9%
 
538118.9%
 
ValueCountFrequency (%) 
538118.9%
 
442719.9%
 
31281429.8%
 
2515912.0%
 
1476211.1%
 
041839.7%
 

KBA13_BMW
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean3.194
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:05.551521image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.015223701
Coefficient of variation (CV)0.3178533815
Kurtosis-0.3417770089
Mean3.194
Median Absolute Deviation (MAD)1
Skewness-0.02129675617
Sum111790
Variance1.030679162
MonotocityNot monotonic
2020-11-30T23:57:05.637510image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31486634.6%
 
4830619.3%
 
2607614.1%
 
540169.3%
 
117364.0%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
117364.0%
 
2607614.1%
 
31486634.6%
 
4830619.3%
 
540169.3%
 
ValueCountFrequency (%) 
540169.3%
 
4830619.3%
 
31486634.6%
 
2607614.1%
 
117364.0%
 

KBA13_CCM_0_1400
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean2.238342857
Minimum0
Maximum5
Zeros6654
Zeros (%)15.5%
Memory size335.8 KiB
2020-11-30T23:57:05.733579image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q33
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.438429828
Coefficient of variation (CV)0.6426315895
Kurtosis-0.7262770607
Mean2.238342857
Median Absolute Deviation (MAD)1
Skewness-0.09732439064
Sum78342
Variance2.06908037
MonotocityNot monotonic
2020-11-30T23:57:05.816120image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31140626.5%
 
2838319.5%
 
0665415.5%
 
432597.6%
 
130427.1%
 
522565.3%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
0665415.5%
 
130427.1%
 
2838319.5%
 
31140626.5%
 
432597.6%
 
522565.3%
 
ValueCountFrequency (%) 
522565.3%
 
432597.6%
 
31140626.5%
 
2838319.5%
 
130427.1%
 
0665415.5%
 

KBA13_CCM_1000
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean2.348085714
Minimum0
Maximum5
Zeros4518
Zeros (%)10.5%
Memory size335.8 KiB
2020-11-30T23:57:05.893864image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median3
Q33
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.407228807
Coefficient of variation (CV)0.5993089598
Kurtosis-0.7095739012
Mean2.348085714
Median Absolute Deviation (MAD)1
Skewness-0.0579613174
Sum82183
Variance1.980292915
MonotocityNot monotonic
2020-11-30T23:57:05.977159image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31262629.4%
 
2600714.0%
 
1591513.8%
 
0451810.5%
 
432947.7%
 
526406.1%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
0451810.5%
 
1591513.8%
 
2600714.0%
 
31262629.4%
 
432947.7%
 
526406.1%
 
ValueCountFrequency (%) 
526406.1%
 
432947.7%
 
31262629.4%
 
2600714.0%
 
1591513.8%
 
0451810.5%
 

KBA13_CCM_1200
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean2.260942857
Minimum0
Maximum5
Zeros6800
Zeros (%)15.8%
Memory size335.8 KiB
2020-11-30T23:57:06.057466image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median3
Q33
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.457021735
Coefficient of variation (CV)0.6444310305
Kurtosis-0.7821499147
Mean2.260942857
Median Absolute Deviation (MAD)1
Skewness-0.1358785767
Sum79133
Variance2.122912337
MonotocityNot monotonic
2020-11-30T23:57:06.140886image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31203628.0%
 
2738917.2%
 
0680015.8%
 
434248.0%
 
130517.1%
 
523005.4%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
0680015.8%
 
130517.1%
 
2738917.2%
 
31203628.0%
 
434248.0%
 
523005.4%
 
ValueCountFrequency (%) 
523005.4%
 
434248.0%
 
31203628.0%
 
2738917.2%
 
130517.1%
 
0680015.8%
 

KBA13_CCM_1400
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean2.982228571
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:06.223751image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation0.9564496995
Coefficient of variation (CV)0.3207164295
Kurtosis-0.1067780232
Mean2.982228571
Median Absolute Deviation (MAD)1
Skewness0.0446479153
Sum104378
Variance0.9147960276
MonotocityNot monotonic
2020-11-30T23:57:06.310398image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31613937.6%
 
2759417.7%
 
4687816.0%
 
522185.2%
 
121715.1%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
121715.1%
 
2759417.7%
 
31613937.6%
 
4687816.0%
 
522185.2%
 
ValueCountFrequency (%) 
522185.2%
 
4687816.0%
 
31613937.6%
 
2759417.7%
 
121715.1%
 

KBA13_CCM_1401_2500
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean2.975514286
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:06.403337image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation0.9508330156
Coefficient of variation (CV)0.3195524956
Kurtosis-0.1342482016
Mean2.975514286
Median Absolute Deviation (MAD)1
Skewness-0.09340853488
Sum104143
Variance0.9040834236
MonotocityNot monotonic
2020-11-30T23:57:06.490204image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31601237.3%
 
4766617.8%
 
2709716.5%
 
124695.7%
 
517564.1%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
124695.7%
 
2709716.5%
 
31601237.3%
 
4766617.8%
 
517564.1%
 
ValueCountFrequency (%) 
517564.1%
 
4766617.8%
 
31601237.3%
 
2709716.5%
 
124695.7%
 

KBA13_CCM_1500
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean2.629228571
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:06.583683image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.416207257
Coefficient of variation (CV)0.53863984
Kurtosis-1.439356501
Mean2.629228571
Median Absolute Deviation (MAD)1
Skewness0.09867064043
Sum92023
Variance2.005642995
MonotocityNot monotonic
2020-11-30T23:57:06.666585image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
11262029.4%
 
4907421.1%
 
3717416.7%
 
531077.2%
 
230257.0%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
11262029.4%
 
230257.0%
 
3717416.7%
 
4907421.1%
 
531077.2%
 
ValueCountFrequency (%) 
531077.2%
 
4907421.1%
 
3717416.7%
 
230257.0%
 
11262029.4%
 

KBA13_CCM_1600
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean3.0326
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:06.756641image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation0.9524211329
Coefficient of variation (CV)0.3140609157
Kurtosis-0.1392026806
Mean3.0326
Median Absolute Deviation (MAD)1
Skewness0.069548996
Sum106141
Variance0.9071060145
MonotocityNot monotonic
2020-11-30T23:57:06.843127image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31598337.2%
 
2748817.4%
 
4727316.9%
 
524675.7%
 
117894.2%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
117894.2%
 
2748817.4%
 
31598337.2%
 
4727316.9%
 
524675.7%
 
ValueCountFrequency (%) 
524675.7%
 
4727316.9%
 
31598337.2%
 
2748817.4%
 
117894.2%
 

KBA13_CCM_1800
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean2.3902
Minimum0
Maximum5
Zeros5981
Zeros (%)13.9%
Memory size335.8 KiB
2020-11-30T23:57:06.932542image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median3
Q33
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.438035431
Coefficient of variation (CV)0.6016381186
Kurtosis-0.6317465486
Mean2.3902
Median Absolute Deviation (MAD)1
Skewness-0.2170560403
Sum83657
Variance2.067945901
MonotocityNot monotonic
2020-11-30T23:57:07.016627image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31241528.9%
 
2783518.2%
 
0598113.9%
 
437838.8%
 
526566.2%
 
123305.4%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
0598113.9%
 
123305.4%
 
2783518.2%
 
31241528.9%
 
437838.8%
 
526566.2%
 
ValueCountFrequency (%) 
526566.2%
 
437838.8%
 
31241528.9%
 
2783518.2%
 
123305.4%
 
0598113.9%
 

KBA13_CCM_2000
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean3.121857143
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:07.101810image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9498598621
Coefficient of variation (CV)0.3042611557
Kurtosis-0.1704265907
Mean3.121857143
Median Absolute Deviation (MAD)1
Skewness0.04867643955
Sum109265
Variance0.9022337577
MonotocityNot monotonic
2020-11-30T23:57:07.187455image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31591437.0%
 
4804018.7%
 
2670915.6%
 
529026.8%
 
114353.3%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
114353.3%
 
2670915.6%
 
31591437.0%
 
4804018.7%
 
529026.8%
 
ValueCountFrequency (%) 
529026.8%
 
4804018.7%
 
31591437.0%
 
2670915.6%
 
114353.3%
 

KBA13_CCM_2500
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean2.505171429
Minimum0
Maximum5
Zeros4153
Zeros (%)9.7%
Memory size335.8 KiB
2020-11-30T23:57:07.280094image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median3
Q33
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.425814022
Coefficient of variation (CV)0.569148285
Kurtosis-0.6608483219
Mean2.505171429
Median Absolute Deviation (MAD)1
Skewness-0.1504066803
Sum87681
Variance2.032945626
MonotocityNot monotonic
2020-11-30T23:57:07.363431image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31260829.3%
 
2617714.4%
 
1469510.9%
 
041539.7%
 
440279.4%
 
533407.8%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
041539.7%
 
1469510.9%
 
2617714.4%
 
31260829.3%
 
440279.4%
 
533407.8%
 
ValueCountFrequency (%) 
533407.8%
 
440279.4%
 
31260829.3%
 
2617714.4%
 
1469510.9%
 
041539.7%
 

KBA13_CCM_2501
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean2.532428571
Minimum0
Maximum5
Zeros3906
Zeros (%)9.1%
Memory size335.8 KiB
2020-11-30T23:57:07.441873image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median3
Q33
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.443718195
Coefficient of variation (CV)0.5700923655
Kurtosis-0.7309348543
Mean2.532428571
Median Absolute Deviation (MAD)1
Skewness-0.1429879731
Sum88635
Variance2.084322226
MonotocityNot monotonic
2020-11-30T23:57:07.525399image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31281829.8%
 
1543312.6%
 
2512411.9%
 
440959.5%
 
039069.1%
 
536248.4%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
039069.1%
 
1543312.6%
 
2512411.9%
 
31281829.8%
 
440959.5%
 
536248.4%
 
ValueCountFrequency (%) 
536248.4%
 
440959.5%
 
31281829.8%
 
2512411.9%
 
1543312.6%
 
039069.1%
 

KBA13_CCM_3000
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean2.593257143
Minimum0
Maximum5
Zeros2500
Zeros (%)5.8%
Memory size335.8 KiB
2020-11-30T23:57:07.603703image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median3
Q33
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.375910107
Coefficient of variation (CV)0.5305721845
Kurtosis-0.6676067917
Mean2.593257143
Median Absolute Deviation (MAD)1
Skewness-0.09617638692
Sum90764
Variance1.893128623
MonotocityNot monotonic
2020-11-30T23:57:07.688156image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31332431.0%
 
1654015.2%
 
2493811.5%
 
441149.6%
 
535848.3%
 
025005.8%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
025005.8%
 
1654015.2%
 
2493811.5%
 
31332431.0%
 
441149.6%
 
535848.3%
 
ValueCountFrequency (%) 
535848.3%
 
441149.6%
 
31332431.0%
 
2493811.5%
 
1654015.2%
 
025005.8%
 

KBA13_CCM_3001
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean2.613114286
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:07.771413image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.513373439
Coefficient of variation (CV)0.5791455229
Kurtosis-1.583052091
Mean2.613114286
Median Absolute Deviation (MAD)2
Skewness0.1043177759
Sum91459
Variance2.290299167
MonotocityNot monotonic
2020-11-30T23:57:07.859884image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
11523635.5%
 
4941821.9%
 
3658515.3%
 
537588.7%
 
23< 0.1%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
11523635.5%
 
23< 0.1%
 
3658515.3%
 
4941821.9%
 
537588.7%
 
ValueCountFrequency (%) 
537588.7%
 
4941821.9%
 
3658515.3%
 
23< 0.1%
 
11523635.5%
 

KBA13_FAB_ASIEN
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean2.950142857
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:07.953867image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.033372663
Coefficient of variation (CV)0.3502788554
Kurtosis-0.3283458958
Mean2.950142857
Median Absolute Deviation (MAD)1
Skewness0.05073712197
Sum103255
Variance1.067859061
MonotocityNot monotonic
2020-11-30T23:57:08.038625image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31487034.6%
 
2773418.0%
 
4661915.4%
 
130467.1%
 
527316.4%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
130467.1%
 
2773418.0%
 
31487034.6%
 
4661915.4%
 
527316.4%
 
ValueCountFrequency (%) 
527316.4%
 
4661915.4%
 
31487034.6%
 
2773418.0%
 
130467.1%
 

KBA13_FAB_SONSTIGE
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean2.982314286
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:08.129961image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.021358979
Coefficient of variation (CV)0.3424719466
Kurtosis-0.3015574961
Mean2.982314286
Median Absolute Deviation (MAD)1
Skewness0.03696423327
Sum104381
Variance1.043174163
MonotocityNot monotonic
2020-11-30T23:57:08.214572image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31503335.0%
 
2754417.6%
 
4690516.1%
 
527646.4%
 
127546.4%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
127546.4%
 
2754417.6%
 
31503335.0%
 
4690516.1%
 
527646.4%
 
ValueCountFrequency (%) 
527646.4%
 
4690516.1%
 
31503335.0%
 
2754417.6%
 
127546.4%
 

KBA13_FIAT
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean3.0914
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:08.306484image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.020247201
Coefficient of variation (CV)0.3300275607
Kurtosis-0.3333882526
Mean3.0914
Median Absolute Deviation (MAD)1
Skewness0.03871812825
Sum108199
Variance1.040904352
MonotocityNot monotonic
2020-11-30T23:57:08.390636image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31496334.8%
 
4746117.4%
 
2701416.3%
 
534698.1%
 
120934.9%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
120934.9%
 
2701416.3%
 
31496334.8%
 
4746117.4%
 
534698.1%
 
ValueCountFrequency (%) 
534698.1%
 
4746117.4%
 
31496334.8%
 
2701416.3%
 
120934.9%
 

KBA13_FORD
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean2.931828571
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:08.483827image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.064095528
Coefficient of variation (CV)0.3629460258
Kurtosis-0.3979973466
Mean2.931828571
Median Absolute Deviation (MAD)1
Skewness0.08167181874
Sum102614
Variance1.132299293
MonotocityNot monotonic
2020-11-30T23:57:08.569739image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31448933.7%
 
2785418.3%
 
4623014.5%
 
134047.9%
 
530237.0%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
134047.9%
 
2785418.3%
 
31448933.7%
 
4623014.5%
 
530237.0%
 
ValueCountFrequency (%) 
530237.0%
 
4623014.5%
 
31448933.7%
 
2785418.3%
 
134047.9%
 

KBA13_GBZ
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean3.459542857
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:08.661394image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.102360168
Coefficient of variation (CV)0.3186433044
Kurtosis-0.5878453432
Mean3.459542857
Median Absolute Deviation (MAD)1
Skewness-0.2289319351
Sum121084
Variance1.21519794
MonotocityNot monotonic
2020-11-30T23:57:08.743373image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31269329.5%
 
4872420.3%
 
5753717.5%
 
2437810.2%
 
116683.9%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
116683.9%
 
2437810.2%
 
31269329.5%
 
4872420.3%
 
5753717.5%
 
ValueCountFrequency (%) 
5753717.5%
 
4872420.3%
 
31269329.5%
 
2437810.2%
 
116683.9%
 

KBA13_HALTER_20
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean2.9078
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:08.833447image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.013741278
Coefficient of variation (CV)0.3486282682
Kurtosis-0.2987523673
Mean2.9078
Median Absolute Deviation (MAD)1
Skewness0.06053365915
Sum101773
Variance1.027671379
MonotocityNot monotonic
2020-11-30T23:57:08.926519image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31488434.6%
 
2822319.1%
 
4651015.2%
 
130707.1%
 
523135.4%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
130707.1%
 
2822319.1%
 
31488434.6%
 
4651015.2%
 
523135.4%
 
ValueCountFrequency (%) 
523135.4%
 
4651015.2%
 
31488434.6%
 
2822319.1%
 
130707.1%
 

KBA13_HALTER_25
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean2.887457143
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:09.020243image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.055527056
Coefficient of variation (CV)0.3655559213
Kurtosis-0.3822183886
Mean2.887457143
Median Absolute Deviation (MAD)1
Skewness0.05350973845
Sum101061
Variance1.114137366
MonotocityNot monotonic
2020-11-30T23:57:09.103984image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31462834.0%
 
2779918.2%
 
4621814.5%
 
137678.8%
 
525886.0%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
137678.8%
 
2779918.2%
 
31462834.0%
 
4621814.5%
 
525886.0%
 
ValueCountFrequency (%) 
525886.0%
 
4621814.5%
 
31462834.0%
 
2779918.2%
 
137678.8%
 

KBA13_HALTER_30
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean2.970142857
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:09.195406image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.07052651
Coefficient of variation (CV)0.3604292997
Kurtosis-0.4193454718
Mean2.970142857
Median Absolute Deviation (MAD)1
Skewness0.02218698206
Sum103955
Variance1.146027009
MonotocityNot monotonic
2020-11-30T23:57:09.279847image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31450333.8%
 
2723116.8%
 
4671815.6%
 
134077.9%
 
531417.3%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
134077.9%
 
2723116.8%
 
31450333.8%
 
4671815.6%
 
531417.3%
 
ValueCountFrequency (%) 
531417.3%
 
4671815.6%
 
31450333.8%
 
2723116.8%
 
134077.9%
 

KBA13_HALTER_35
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean3.028942857
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:09.371951image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.087945173
Coefficient of variation (CV)0.3591831291
Kurtosis-0.4976550068
Mean3.028942857
Median Absolute Deviation (MAD)1
Skewness-0.0178133411
Sum106013
Variance1.1836247
MonotocityNot monotonic
2020-11-30T23:57:09.456519image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31388232.3%
 
4737917.2%
 
2696016.2%
 
535388.2%
 
132417.5%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
132417.5%
 
2696016.2%
 
31388232.3%
 
4737917.2%
 
535388.2%
 
ValueCountFrequency (%) 
535388.2%
 
4737917.2%
 
31388232.3%
 
2696016.2%
 
132417.5%
 

KBA13_HALTER_40
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean3.021571429
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:09.548577image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.08261437
Coefficient of variation (CV)0.3582951441
Kurtosis-0.4685546533
Mean3.021571429
Median Absolute Deviation (MAD)1
Skewness0.001802021364
Sum105755
Variance1.172053875
MonotocityNot monotonic
2020-11-30T23:57:09.634859image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31415933.0%
 
4710216.5%
 
2700716.3%
 
535318.2%
 
132017.5%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
132017.5%
 
2700716.3%
 
31415933.0%
 
4710216.5%
 
535318.2%
 
ValueCountFrequency (%) 
535318.2%
 
4710216.5%
 
31415933.0%
 
2700716.3%
 
132017.5%
 

KBA13_HALTER_45
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean2.984857143
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:09.726255image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.089943147
Coefficient of variation (CV)0.3651575587
Kurtosis-0.49733019
Mean2.984857143
Median Absolute Deviation (MAD)1
Skewness0.02575192571
Sum104470
Variance1.187976065
MonotocityNot monotonic
2020-11-30T23:57:09.810355image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31391632.4%
 
2735817.1%
 
4689216.0%
 
134338.0%
 
534017.9%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
134338.0%
 
2735817.1%
 
31391632.4%
 
4689216.0%
 
534017.9%
 
ValueCountFrequency (%) 
534017.9%
 
4689216.0%
 
31391632.4%
 
2735817.1%
 
134338.0%
 

KBA13_HALTER_50
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean2.9036
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:09.901969image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.075757589
Coefficient of variation (CV)0.3704909729
Kurtosis-0.4517009097
Mean2.9036
Median Absolute Deviation (MAD)1
Skewness0.07575972473
Sum101626
Variance1.15725439
MonotocityNot monotonic
2020-11-30T23:57:09.989240image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31407132.8%
 
2799018.6%
 
4630614.7%
 
137398.7%
 
528946.7%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
137398.7%
 
2799018.6%
 
31407132.8%
 
4630614.7%
 
528946.7%
 
ValueCountFrequency (%) 
528946.7%
 
4630614.7%
 
31407132.8%
 
2799018.6%
 
137398.7%
 

KBA13_HALTER_55
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean2.901085714
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:10.080581image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.075927724
Coefficient of variation (CV)0.3708707119
Kurtosis-0.4488370122
Mean2.901085714
Median Absolute Deviation (MAD)1
Skewness0.07590333698
Sum101538
Variance1.157620468
MonotocityNot monotonic
2020-11-30T23:57:10.164724image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31410732.8%
 
2796918.5%
 
4626914.6%
 
137688.8%
 
528876.7%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
137688.8%
 
2796918.5%
 
31410732.8%
 
4626914.6%
 
528876.7%
 
ValueCountFrequency (%) 
528876.7%
 
4626914.6%
 
31410732.8%
 
2796918.5%
 
137688.8%
 

KBA13_HALTER_60
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean2.971257143
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:10.255909image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.06827265
Coefficient of variation (CV)0.3595355765
Kurtosis-0.4259868023
Mean2.971257143
Median Absolute Deviation (MAD)1
Skewness0.04928788586
Sum103994
Variance1.141206454
MonotocityNot monotonic
2020-11-30T23:57:10.340285image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31435633.4%
 
2754817.6%
 
4665415.5%
 
132497.6%
 
531937.4%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
132497.6%
 
2754817.6%
 
31435633.4%
 
4665415.5%
 
531937.4%
 
ValueCountFrequency (%) 
531937.4%
 
4665415.5%
 
31435633.4%
 
2754817.6%
 
132497.6%
 

KBA13_HALTER_65
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean3.150542857
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:10.431125image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.066033048
Coefficient of variation (CV)0.3383648777
Kurtosis-0.4559867838
Mean3.150542857
Median Absolute Deviation (MAD)1
Skewness-0.02838339118
Sum110269
Variance1.13642646
MonotocityNot monotonic
2020-11-30T23:57:10.514820image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31421233.1%
 
4779718.1%
 
2639814.9%
 
542649.9%
 
123295.4%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
123295.4%
 
2639814.9%
 
31421233.1%
 
4779718.1%
 
542649.9%
 
ValueCountFrequency (%) 
542649.9%
 
4779718.1%
 
31421233.1%
 
2639814.9%
 
123295.4%
 

KBA13_HALTER_66
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean3.133485714
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:10.606247image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.09848677
Coefficient of variation (CV)0.3505638353
Kurtosis-0.5247769901
Mean3.133485714
Median Absolute Deviation (MAD)1
Skewness-0.06090870467
Sum109672
Variance1.206673183
MonotocityNot monotonic
2020-11-30T23:57:10.690234image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31371731.9%
 
4779918.2%
 
2629314.6%
 
5438710.2%
 
128046.5%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
128046.5%
 
2629314.6%
 
31371731.9%
 
4779918.2%
 
5438710.2%
 
ValueCountFrequency (%) 
5438710.2%
 
4779918.2%
 
31371731.9%
 
2629314.6%
 
128046.5%
 

KBA13_HERST_ASIEN
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean2.965485714
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:10.781129image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.062227243
Coefficient of variation (CV)0.3581967157
Kurtosis-0.3972262809
Mean2.965485714
Median Absolute Deviation (MAD)1
Skewness0.0518384444
Sum103792
Variance1.128326716
MonotocityNot monotonic
2020-11-30T23:57:10.865489image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31457233.9%
 
2751617.5%
 
4654415.2%
 
132437.5%
 
531257.3%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
132437.5%
 
2751617.5%
 
31457233.9%
 
4654415.2%
 
531257.3%
 
ValueCountFrequency (%) 
531257.3%
 
4654415.2%
 
31457233.9%
 
2751617.5%
 
132437.5%
 

KBA13_HERST_AUDI_VW
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean2.983571429
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:10.959082image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.022665976
Coefficient of variation (CV)0.3427657088
Kurtosis-0.2889879182
Mean2.983571429
Median Absolute Deviation (MAD)1
Skewness-0.001464359043
Sum104425
Variance1.045845698
MonotocityNot monotonic
2020-11-30T23:57:11.043336image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31519335.4%
 
2717616.7%
 
4702916.4%
 
129086.8%
 
526946.3%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
129086.8%
 
2717616.7%
 
31519335.4%
 
4702916.4%
 
526946.3%
 
ValueCountFrequency (%) 
526946.3%
 
4702916.4%
 
31519335.4%
 
2717616.7%
 
129086.8%
 

KBA13_HERST_BMW_BENZ
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean3.198085714
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:11.136505image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.062648994
Coefficient of variation (CV)0.3322765833
Kurtosis-0.4369751931
Mean3.198085714
Median Absolute Deviation (MAD)1
Skewness-0.07260514846
Sum111933
Variance1.129222885
MonotocityNot monotonic
2020-11-30T23:57:11.230971image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31421133.1%
 
4821419.1%
 
2587313.7%
 
5449910.5%
 
122035.1%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
122035.1%
 
2587313.7%
 
31421133.1%
 
4821419.1%
 
5449910.5%
 
ValueCountFrequency (%) 
5449910.5%
 
4821419.1%
 
31421133.1%
 
2587313.7%
 
122035.1%
 

KBA13_HERST_EUROPA
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean3.0742
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:11.324306image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.027804303
Coefficient of variation (CV)0.3343322825
Kurtosis-0.3210464445
Mean3.0742
Median Absolute Deviation (MAD)1
Skewness0.01338664362
Sum107597
Variance1.056381685
MonotocityNot monotonic
2020-11-30T23:57:11.410003image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31504335.0%
 
4738317.2%
 
2683815.9%
 
533817.9%
 
123555.5%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
123555.5%
 
2683815.9%
 
31504335.0%
 
4738317.2%
 
533817.9%
 
ValueCountFrequency (%) 
533817.9%
 
4738317.2%
 
31504335.0%
 
2683815.9%
 
123555.5%
 

KBA13_HERST_FORD_OPEL
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean2.886542857
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:11.502802image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.06933364
Coefficient of variation (CV)0.3704547941
Kurtosis-0.421913971
Mean2.886542857
Median Absolute Deviation (MAD)1
Skewness0.07809584854
Sum101029
Variance1.143474433
MonotocityNot monotonic
2020-11-30T23:57:11.588444image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31429933.3%
 
2798118.6%
 
4613014.3%
 
138258.9%
 
527656.4%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
138258.9%
 
2798118.6%
 
31429933.3%
 
4613014.3%
 
527656.4%
 
ValueCountFrequency (%) 
527656.4%
 
4613014.3%
 
31429933.3%
 
2798118.6%
 
138258.9%
 

KBA13_HERST_SONST
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean2.982314286
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:11.680263image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.021358979
Coefficient of variation (CV)0.3424719466
Kurtosis-0.3015574961
Mean2.982314286
Median Absolute Deviation (MAD)1
Skewness0.03696423327
Sum104381
Variance1.043174163
MonotocityNot monotonic
2020-11-30T23:57:11.764393image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31503335.0%
 
2754417.6%
 
4690516.1%
 
527646.4%
 
127546.4%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
127546.4%
 
2754417.6%
 
31503335.0%
 
4690516.1%
 
527646.4%
 
ValueCountFrequency (%) 
527646.4%
 
4690516.1%
 
31503335.0%
 
2754417.6%
 
127546.4%
 

KBA13_HHZ
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean3.4982
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:11.856582image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9665375729
Coefficient of variation (CV)0.2762956872
Kurtosis-0.4850503752
Mean3.4982
Median Absolute Deviation (MAD)1
Skewness0.001196455547
Sum122437
Variance0.9341948799
MonotocityNot monotonic
2020-11-30T23:57:11.943939image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31520535.4%
 
4905221.1%
 
5658115.3%
 
235478.3%
 
16151.4%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
16151.4%
 
235478.3%
 
31520535.4%
 
4905221.1%
 
5658115.3%
 
ValueCountFrequency (%) 
5658115.3%
 
4905221.1%
 
31520535.4%
 
235478.3%
 
16151.4%
 

KBA13_KMH_0_140
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean2.244
Minimum0
Maximum5
Zeros4632
Zeros (%)10.8%
Memory size335.8 KiB
2020-11-30T23:57:12.031565image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median3
Q33
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.523703774
Coefficient of variation (CV)0.679012377
Kurtosis-1.133511669
Mean2.244
Median Absolute Deviation (MAD)2
Skewness0.1097384947
Sum78540
Variance2.321673191
MonotocityNot monotonic
2020-11-30T23:57:12.115801image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31237928.8%
 
11094725.5%
 
0463210.8%
 
438158.9%
 
529146.8%
 
23130.7%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
0463210.8%
 
11094725.5%
 
23130.7%
 
31237928.8%
 
438158.9%
 
529146.8%
 
ValueCountFrequency (%) 
529146.8%
 
438158.9%
 
31237928.8%
 
23130.7%
 
11094725.5%
 
0463210.8%
 

KBA13_KMH_110
Categorical

MISSING

Distinct3
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Memory size335.8 KiB
1
27949 
3
3922 
2
3129 
ValueCountFrequency (%) 
12794965.1%
 
339229.1%
 
231297.3%
 
(Missing)796218.5%
 
2020-11-30T23:57:12.209998image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters7
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
.3500027.2%
 
03500027.2%
 
12794921.7%
 
n1592412.4%
 
a79626.2%
 
339223.0%
 
231292.4%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number7000054.3%
 
Other Punctuation3500027.2%
 
Lowercase Letter2388618.5%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
03500050.0%
 
12794939.9%
 
339225.6%
 
231294.5%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
.35000100.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n1592466.7%
 
a796233.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Common10500081.5%
 
Latin2388618.5%
 

Most frequent Common characters

ValueCountFrequency (%) 
.3500033.3%
 
03500033.3%
 
12794926.6%
 
339223.7%
 
231293.0%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n1592466.7%
 
a796233.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII128886100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
.3500027.2%
 
03500027.2%
 
12794921.7%
 
n1592412.4%
 
a79626.2%
 
339223.0%
 
231292.4%
 

KBA13_KMH_140
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean2.628828571
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:12.293563image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.378249527
Coefficient of variation (CV)0.5242827706
Kurtosis-1.350824235
Mean2.628828571
Median Absolute Deviation (MAD)1
Skewness0.126740864
Sum92009
Variance1.899571758
MonotocityNot monotonic
2020-11-30T23:57:12.375356image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
11157426.9%
 
4846919.7%
 
3753117.5%
 
2438810.2%
 
530387.1%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
11157426.9%
 
2438810.2%
 
3753117.5%
 
4846919.7%
 
530387.1%
 
ValueCountFrequency (%) 
530387.1%
 
4846919.7%
 
3753117.5%
 
2438810.2%
 
11157426.9%
 

KBA13_KMH_140_210
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean2.844371429
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:12.464965image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q33
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9875549379
Coefficient of variation (CV)0.3471961952
Kurtosis-0.1907808435
Mean2.844371429
Median Absolute Deviation (MAD)1
Skewness0.01908451873
Sum99553
Variance0.9752647553
MonotocityNot monotonic
2020-11-30T23:57:12.552146image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31579636.8%
 
2803318.7%
 
4591213.8%
 
134618.1%
 
517984.2%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
134618.1%
 
2803318.7%
 
31579636.8%
 
4591213.8%
 
517984.2%
 
ValueCountFrequency (%) 
517984.2%
 
4591213.8%
 
31579636.8%
 
2803318.7%
 
134618.1%
 

KBA13_KMH_180
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean2.866714286
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:12.645118image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q33
95-th percentile4
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9760587634
Coefficient of variation (CV)0.3404799593
Kurtosis-0.1899484765
Mean2.866714286
Median Absolute Deviation (MAD)1
Skewness0.003945527833
Sum100335
Variance0.9526907095
MonotocityNot monotonic
2020-11-30T23:57:12.730351image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31573236.6%
 
2808018.8%
 
4628914.6%
 
131687.4%
 
517314.0%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
131687.4%
 
2808018.8%
 
31573236.6%
 
4628914.6%
 
517314.0%
 
ValueCountFrequency (%) 
517314.0%
 
4628914.6%
 
31573236.6%
 
2808018.8%
 
131687.4%
 

KBA13_KMH_210
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean3.104828571
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:12.825355image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9642660241
Coefficient of variation (CV)0.3105698115
Kurtosis-0.156153554
Mean3.104828571
Median Absolute Deviation (MAD)1
Skewness0.01416821725
Sum108669
Variance0.9298089652
MonotocityNot monotonic
2020-11-30T23:57:12.911138image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31593637.1%
 
4788118.3%
 
2656215.3%
 
528986.7%
 
117234.0%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
117234.0%
 
2656215.3%
 
31593637.1%
 
4788118.3%
 
528986.7%
 
ValueCountFrequency (%) 
528986.7%
 
4788118.3%
 
31593637.1%
 
2656215.3%
 
117234.0%
 

KBA13_KMH_211
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean2.496114286
Minimum0
Maximum5
Zeros5978
Zeros (%)13.9%
Memory size335.8 KiB
2020-11-30T23:57:13.002648image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median3
Q33
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.501063668
Coefficient of variation (CV)0.6013601527
Kurtosis-0.7015445236
Mean2.496114286
Median Absolute Deviation (MAD)1
Skewness-0.2377341883
Sum87364
Variance2.253192135
MonotocityNot monotonic
2020-11-30T23:57:13.085702image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31240928.9%
 
2681615.9%
 
0597813.9%
 
440209.4%
 
536628.5%
 
121154.9%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
0597813.9%
 
121154.9%
 
2681615.9%
 
31240928.9%
 
440209.4%
 
536628.5%
 
ValueCountFrequency (%) 
536628.5%
 
440209.4%
 
31240928.9%
 
2681615.9%
 
121154.9%
 
0597813.9%
 

KBA13_KMH_250
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean2.4954
Minimum0
Maximum5
Zeros5985
Zeros (%)13.9%
Memory size335.8 KiB
2020-11-30T23:57:13.163866image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median3
Q33
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.500966472
Coefficient of variation (CV)0.6014933367
Kurtosis-0.7006080031
Mean2.4954
Median Absolute Deviation (MAD)1
Skewness-0.2373950975
Sum87339
Variance2.252900351
MonotocityNot monotonic
2020-11-30T23:57:13.247598image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31241728.9%
 
2682715.9%
 
0598513.9%
 
440059.3%
 
536628.5%
 
121044.9%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
0598513.9%
 
121044.9%
 
2682715.9%
 
31241728.9%
 
440059.3%
 
536628.5%
 
ValueCountFrequency (%) 
536628.5%
 
440059.3%
 
31241728.9%
 
2682715.9%
 
121044.9%
 
0598513.9%
 

KBA13_KMH_251
Categorical

MISSING

Distinct3
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Memory size335.8 KiB
1
29950 
3
4595 
2
 
455
ValueCountFrequency (%) 
12995069.7%
 
3459510.7%
 
24551.1%
 
(Missing)796218.5%
 
2020-11-30T23:57:13.346896image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters7
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
.3500027.2%
 
03500027.2%
 
12995023.2%
 
n1592412.4%
 
a79626.2%
 
345953.6%
 
24550.4%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number7000054.3%
 
Other Punctuation3500027.2%
 
Lowercase Letter2388618.5%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
03500050.0%
 
12995042.8%
 
345956.6%
 
24550.7%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
.35000100.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n1592466.7%
 
a796233.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Common10500081.5%
 
Latin2388618.5%
 

Most frequent Common characters

ValueCountFrequency (%) 
.3500033.3%
 
03500033.3%
 
12995028.5%
 
345954.4%
 
24550.4%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n1592466.7%
 
a796233.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII128886100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
.3500027.2%
 
03500027.2%
 
12995023.2%
 
n1592412.4%
 
a79626.2%
 
345953.6%
 
24550.4%
 

KBA13_KRSAQUOT
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean3.007028571
Minimum0
Maximum5
Zeros4
Zeros (%)< 0.1%
Memory size335.8 KiB
2020-11-30T23:57:13.431264image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.04568999
Coefficient of variation (CV)0.3477486047
Kurtosis-0.3547459633
Mean3.007028571
Median Absolute Deviation (MAD)1
Skewness0.003674275742
Sum105246
Variance1.093467555
MonotocityNot monotonic
2020-11-30T23:57:13.516049image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31479634.4%
 
2709916.5%
 
4708916.5%
 
530737.2%
 
129396.8%
 
04< 0.1%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
04< 0.1%
 
129396.8%
 
2709916.5%
 
31479634.4%
 
4708916.5%
 
530737.2%
 
ValueCountFrequency (%) 
530737.2%
 
4708916.5%
 
31479634.4%
 
2709916.5%
 
129396.8%
 
04< 0.1%
 

KBA13_KRSHERST_AUDI_VW
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean3.015542857
Minimum0
Maximum5
Zeros4
Zeros (%)< 0.1%
Memory size335.8 KiB
2020-11-30T23:57:13.597572image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.018634693
Coefficient of variation (CV)0.3377947988
Kurtosis-0.324204703
Mean3.015542857
Median Absolute Deviation (MAD)1
Skewness-0.03188613928
Sum105544
Variance1.037616637
MonotocityNot monotonic
2020-11-30T23:57:13.682401image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31475534.3%
 
4771318.0%
 
2717916.7%
 
526806.2%
 
126696.2%
 
04< 0.1%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
04< 0.1%
 
126696.2%
 
2717916.7%
 
31475534.3%
 
4771318.0%
 
526806.2%
 
ValueCountFrequency (%) 
526806.2%
 
4771318.0%
 
31475534.3%
 
2717916.7%
 
126696.2%
 
04< 0.1%
 

KBA13_KRSHERST_BMW_BENZ
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean3.124314286
Minimum0
Maximum5
Zeros4
Zeros (%)< 0.1%
Memory size335.8 KiB
2020-11-30T23:57:13.761886image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q13
median3
Q34
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.03121526
Coefficient of variation (CV)0.3300613081
Kurtosis-0.3311796463
Mean3.124314286
Median Absolute Deviation (MAD)1
Skewness0.01494440526
Sum109351
Variance1.063404913
MonotocityNot monotonic
2020-11-30T23:57:13.847089image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31510235.2%
 
4744617.3%
 
2650515.1%
 
538278.9%
 
121164.9%
 
04< 0.1%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
04< 0.1%
 
121164.9%
 
2650515.1%
 
31510235.2%
 
4744617.3%
 
538278.9%
 
ValueCountFrequency (%) 
538278.9%
 
4744617.3%
 
31510235.2%
 
2650515.1%
 
121164.9%
 
04< 0.1%
 

KBA13_KRSHERST_FORD_OPEL
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean2.972114286
Minimum0
Maximum5
Zeros4
Zeros (%)< 0.1%
Memory size335.8 KiB
2020-11-30T23:57:13.928781image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.05621831
Coefficient of variation (CV)0.3553760752
Kurtosis-0.3987383048
Mean2.972114286
Median Absolute Deviation (MAD)1
Skewness-0.01122440687
Sum104024
Variance1.115597118
MonotocityNot monotonic
2020-11-30T23:57:14.013738image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31450333.8%
 
2719516.7%
 
4711716.6%
 
133127.7%
 
528696.7%
 
04< 0.1%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
04< 0.1%
 
133127.7%
 
2719516.7%
 
31450333.8%
 
4711716.6%
 
528696.7%
 
ValueCountFrequency (%) 
528696.7%
 
4711716.6%
 
31450333.8%
 
2719516.7%
 
133127.7%
 
04< 0.1%
 

KBA13_KRSSEG_KLEIN
Categorical

MISSING

Distinct4
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Memory size335.8 KiB
2
32078 
1
 
1664
3
 
1252
0
 
6
ValueCountFrequency (%) 
23207874.7%
 
116643.9%
 
312522.9%
 
06< 0.1%
 
(Missing)796218.5%
 
2020-11-30T23:57:14.110473image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters7
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
03500627.2%
 
.3500027.2%
 
23207824.9%
 
n1592412.4%
 
a79626.2%
 
116641.3%
 
312521.0%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number7000054.3%
 
Other Punctuation3500027.2%
 
Lowercase Letter2388618.5%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
03500650.0%
 
23207845.8%
 
116642.4%
 
312521.8%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
.35000100.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n1592466.7%
 
a796233.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Common10500081.5%
 
Latin2388618.5%
 

Most frequent Common characters

ValueCountFrequency (%) 
03500633.3%
 
.3500033.3%
 
23207830.6%
 
116641.6%
 
312521.2%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n1592466.7%
 
a796233.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII128886100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
03500627.2%
 
.3500027.2%
 
23207824.9%
 
n1592412.4%
 
a79626.2%
 
116641.3%
 
312521.0%
 

KBA13_KRSSEG_OBER
Categorical

MISSING

Distinct4
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Memory size335.8 KiB
2
22912 
1
6605 
3
5468 
0
 
15
ValueCountFrequency (%) 
22291253.3%
 
1660515.4%
 
3546812.7%
 
015< 0.1%
 
(Missing)796218.5%
 
2020-11-30T23:57:14.208038image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters7
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
03501527.2%
 
.3500027.2%
 
22291217.8%
 
n1592412.4%
 
a79626.2%
 
166055.1%
 
354684.2%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number7000054.3%
 
Other Punctuation3500027.2%
 
Lowercase Letter2388618.5%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
03501550.0%
 
22291232.7%
 
166059.4%
 
354687.8%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
.35000100.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n1592466.7%
 
a796233.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Common10500081.5%
 
Latin2388618.5%
 

Most frequent Common characters

ValueCountFrequency (%) 
03501533.3%
 
.3500033.3%
 
22291221.8%
 
166056.3%
 
354685.2%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n1592466.7%
 
a796233.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII128886100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
03501527.2%
 
.3500027.2%
 
22291217.8%
 
n1592412.4%
 
a79626.2%
 
166055.1%
 
354684.2%
 

KBA13_KRSSEG_VAN
Categorical

MISSING

Distinct4
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Memory size335.8 KiB
2
22127 
1
7065 
3
5781 
0
 
27
ValueCountFrequency (%) 
22212751.5%
 
1706516.4%
 
3578113.5%
 
0270.1%
 
(Missing)796218.5%
 
2020-11-30T23:57:14.304265image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters7
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
03502727.2%
 
.3500027.2%
 
22212717.2%
 
n1592412.4%
 
a79626.2%
 
170655.5%
 
357814.5%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number7000054.3%
 
Other Punctuation3500027.2%
 
Lowercase Letter2388618.5%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
03502750.0%
 
22212731.6%
 
1706510.1%
 
357818.3%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
.35000100.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n1592466.7%
 
a796233.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Common10500081.5%
 
Latin2388618.5%
 

Most frequent Common characters

ValueCountFrequency (%) 
03502733.4%
 
.3500033.3%
 
22212721.1%
 
170656.7%
 
357815.5%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n1592466.7%
 
a796233.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII128886100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
03502727.2%
 
.3500027.2%
 
22212717.2%
 
n1592412.4%
 
a79626.2%
 
170655.5%
 
357814.5%
 

KBA13_KRSZUL_NEU
Categorical

MISSING

Distinct4
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Memory size335.8 KiB
2
17080 
1
9113 
3
7798 
0
 
1009
ValueCountFrequency (%) 
21708039.8%
 
1911321.2%
 
3779818.2%
 
010092.3%
 
(Missing)796218.5%
 
2020-11-30T23:57:14.401650image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters7
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
03600927.9%
 
.3500027.2%
 
21708013.3%
 
n1592412.4%
 
191137.1%
 
a79626.2%
 
377986.1%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number7000054.3%
 
Other Punctuation3500027.2%
 
Lowercase Letter2388618.5%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
03600951.4%
 
21708024.4%
 
1911313.0%
 
3779811.1%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
.35000100.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n1592466.7%
 
a796233.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Common10500081.5%
 
Latin2388618.5%
 

Most frequent Common characters

ValueCountFrequency (%) 
03600934.3%
 
.3500033.3%
 
21708016.3%
 
191138.7%
 
377987.4%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n1592466.7%
 
a796233.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII128886100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
03600927.9%
 
.3500027.2%
 
21708013.3%
 
n1592412.4%
 
191137.1%
 
a79626.2%
 
377986.1%
 

KBA13_KW_0_60
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean2.893971429
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:14.490199image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q33
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9698669808
Coefficient of variation (CV)0.3351335715
Kurtosis-0.1538477583
Mean2.893971429
Median Absolute Deviation (MAD)1
Skewness0.02250671059
Sum101289
Variance0.9406419604
MonotocityNot monotonic
2020-11-30T23:57:14.578091image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31586936.9%
 
2804318.7%
 
4636014.8%
 
128716.7%
 
518574.3%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
128716.7%
 
2804318.7%
 
31586936.9%
 
4636014.8%
 
518574.3%
 
ValueCountFrequency (%) 
518574.3%
 
4636014.8%
 
31586936.9%
 
2804318.7%
 
128716.7%
 

KBA13_KW_110
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean2.470428571
Minimum0
Maximum5
Zeros5425
Zeros (%)12.6%
Memory size335.8 KiB
2020-11-30T23:57:14.675300image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median3
Q33
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.445124631
Coefficient of variation (CV)0.5849692023
Kurtosis-0.620242832
Mean2.470428571
Median Absolute Deviation (MAD)1
Skewness-0.2343454077
Sum86465
Variance2.088385199
MonotocityNot monotonic
2020-11-30T23:57:14.757859image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31246729.0%
 
2729917.0%
 
0542512.6%
 
441519.7%
 
530517.1%
 
126076.1%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
0542512.6%
 
126076.1%
 
2729917.0%
 
31246729.0%
 
441519.7%
 
530517.1%
 
ValueCountFrequency (%) 
530517.1%
 
441519.7%
 
31246729.0%
 
2729917.0%
 
126076.1%
 
0542512.6%
 

KBA13_KW_120
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean2.390485714
Minimum0
Maximum5
Zeros3940
Zeros (%)9.2%
Memory size335.8 KiB
2020-11-30T23:57:14.836398image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median3
Q33
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.522484339
Coefficient of variation (CV)0.6368933017
Kurtosis-1.105172237
Mean2.390485714
Median Absolute Deviation (MAD)1
Skewness0.0152637046
Sum83667
Variance2.317958563
MonotocityNot monotonic
2020-11-30T23:57:14.922551image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31228228.6%
 
1985622.9%
 
4439910.2%
 
039409.2%
 
534418.0%
 
210822.5%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
039409.2%
 
1985622.9%
 
210822.5%
 
31228228.6%
 
4439910.2%
 
534418.0%
 
ValueCountFrequency (%) 
534418.0%
 
4439910.2%
 
31228228.6%
 
210822.5%
 
1985622.9%
 
039409.2%
 

KBA13_KW_121
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean2.540857143
Minimum0
Maximum5
Zeros4018
Zeros (%)9.4%
Memory size335.8 KiB
2020-11-30T23:57:15.001285image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median3
Q33
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.443504248
Coefficient of variation (CV)0.5681170435
Kurtosis-0.6973264975
Mean2.540857143
Median Absolute Deviation (MAD)1
Skewness-0.1477194459
Sum88930
Variance2.083704514
MonotocityNot monotonic
2020-11-30T23:57:15.084793image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31250029.1%
 
2582413.6%
 
1485111.3%
 
441049.6%
 
040189.4%
 
537038.6%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
040189.4%
 
1485111.3%
 
2582413.6%
 
31250029.1%
 
441049.6%
 
537038.6%
 
ValueCountFrequency (%) 
537038.6%
 
441049.6%
 
31250029.1%
 
2582413.6%
 
1485111.3%
 
040189.4%
 

KBA13_KW_30
Categorical

MISSING

Distinct3
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Memory size335.8 KiB
1
25064 
2
6396 
3
3540 
ValueCountFrequency (%) 
12506458.3%
 
2639614.9%
 
335408.2%
 
(Missing)796218.5%
 
2020-11-30T23:57:15.180105image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters7
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
.3500027.2%
 
03500027.2%
 
12506419.4%
 
n1592412.4%
 
a79626.2%
 
263965.0%
 
335402.7%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number7000054.3%
 
Other Punctuation3500027.2%
 
Lowercase Letter2388618.5%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
03500050.0%
 
12506435.8%
 
263969.1%
 
335405.1%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
.35000100.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n1592466.7%
 
a796233.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Common10500081.5%
 
Latin2388618.5%
 

Most frequent Common characters

ValueCountFrequency (%) 
.3500033.3%
 
03500033.3%
 
12506423.9%
 
263966.1%
 
335403.4%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n1592466.7%
 
a796233.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII128886100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
.3500027.2%
 
03500027.2%
 
12506419.4%
 
n1592412.4%
 
a79626.2%
 
263965.0%
 
335402.7%
 

KBA13_KW_40
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean2.3016
Minimum0
Maximum5
Zeros4534
Zeros (%)10.6%
Memory size335.8 KiB
2020-11-30T23:57:15.260368image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median3
Q33
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.391753749
Coefficient of variation (CV)0.6046896718
Kurtosis-0.7141680072
Mean2.3016
Median Absolute Deviation (MAD)1
Skewness-0.02682376715
Sum80556
Variance1.936978497
MonotocityNot monotonic
2020-11-30T23:57:15.344432image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31206428.1%
 
2647415.1%
 
1621214.5%
 
0453410.6%
 
433767.9%
 
523405.4%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
0453410.6%
 
1621214.5%
 
2647415.1%
 
31206428.1%
 
433767.9%
 
523405.4%
 
ValueCountFrequency (%) 
523405.4%
 
433767.9%
 
31206428.1%
 
2647415.1%
 
1621214.5%
 
0453410.6%
 

KBA13_KW_50
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean2.273028571
Minimum0
Maximum5
Zeros6649
Zeros (%)15.5%
Memory size335.8 KiB
2020-11-30T23:57:15.423461image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q33
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.43539939
Coefficient of variation (CV)0.631492014
Kurtosis-0.6861838019
Mean2.273028571
Median Absolute Deviation (MAD)1
Skewness-0.1459235187
Sum79556
Variance2.06037141
MonotocityNot monotonic
2020-11-30T23:57:15.506398image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31177727.4%
 
2853719.9%
 
0664915.5%
 
433067.7%
 
124325.7%
 
522995.4%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
0664915.5%
 
124325.7%
 
2853719.9%
 
31177727.4%
 
433067.7%
 
522995.4%
 
ValueCountFrequency (%) 
522995.4%
 
433067.7%
 
31177727.4%
 
2853719.9%
 
124325.7%
 
0664915.5%
 

KBA13_KW_60
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean2.257971429
Minimum0
Maximum5
Zeros6069
Zeros (%)14.1%
Memory size335.8 KiB
2020-11-30T23:57:15.584229image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q33
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.419072028
Coefficient of variation (CV)0.6284720923
Kurtosis-0.7035909971
Mean2.257971429
Median Absolute Deviation (MAD)1
Skewness-0.09672195701
Sum79029
Variance2.013765421
MonotocityNot monotonic
2020-11-30T23:57:15.670406image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31163927.1%
 
2801518.7%
 
0606914.1%
 
137438.7%
 
433317.8%
 
522035.1%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
0606914.1%
 
137438.7%
 
2801518.7%
 
31163927.1%
 
433317.8%
 
522035.1%
 
ValueCountFrequency (%) 
522035.1%
 
433317.8%
 
31163927.1%
 
2801518.7%
 
137438.7%
 
0606914.1%
 

KBA13_KW_61_120
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean3.073228571
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:15.759206image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9604796078
Coefficient of variation (CV)0.3125311331
Kurtosis-0.1212101814
Mean3.073228571
Median Absolute Deviation (MAD)1
Skewness-0.003154055208
Sum107563
Variance0.9225210769
MonotocityNot monotonic
2020-11-30T23:57:15.848620image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31609437.5%
 
4773218.0%
 
2665115.5%
 
526326.1%
 
118914.4%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
118914.4%
 
2665115.5%
 
31609437.5%
 
4773218.0%
 
526326.1%
 
ValueCountFrequency (%) 
526326.1%
 
4773218.0%
 
31609437.5%
 
2665115.5%
 
118914.4%
 

KBA13_KW_70
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean2.330857143
Minimum0
Maximum5
Zeros6422
Zeros (%)14.9%
Memory size335.8 KiB
2020-11-30T23:57:15.940838image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median3
Q33
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.444366005
Coefficient of variation (CV)0.6196716129
Kurtosis-0.6758502079
Mean2.330857143
Median Absolute Deviation (MAD)1
Skewness-0.1830933081
Sum81580
Variance2.086193157
MonotocityNot monotonic
2020-11-30T23:57:16.024635image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31213528.2%
 
2808818.8%
 
0642214.9%
 
435408.2%
 
525065.8%
 
123095.4%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
0642214.9%
 
123095.4%
 
2808818.8%
 
31213528.2%
 
435408.2%
 
525065.8%
 
ValueCountFrequency (%) 
525065.8%
 
435408.2%
 
31213528.2%
 
2808818.8%
 
123095.4%
 
0642214.9%
 

KBA13_KW_80
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean2.3382
Minimum0
Maximum5
Zeros5746
Zeros (%)13.4%
Memory size335.8 KiB
2020-11-30T23:57:16.103433image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median3
Q33
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.424437289
Coefficient of variation (CV)0.6092025013
Kurtosis-0.6604049256
Mean2.3382
Median Absolute Deviation (MAD)1
Skewness-0.1471241492
Sum81837
Variance2.029021589
MonotocityNot monotonic
2020-11-30T23:57:16.186900image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31206428.1%
 
2782618.2%
 
0574613.4%
 
435518.3%
 
133197.7%
 
524945.8%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
0574613.4%
 
133197.7%
 
2782618.2%
 
31206428.1%
 
435518.3%
 
524945.8%
 
ValueCountFrequency (%) 
524945.8%
 
435518.3%
 
31206428.1%
 
2782618.2%
 
133197.7%
 
0574613.4%
 

KBA13_KW_90
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean2.416828571
Minimum0
Maximum5
Zeros5936
Zeros (%)13.8%
Memory size335.8 KiB
2020-11-30T23:57:16.266287image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median3
Q33
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.446730116
Coefficient of variation (CV)0.5986068408
Kurtosis-0.6278961874
Mean2.416828571
Median Absolute Deviation (MAD)1
Skewness-0.227839395
Sum84589
Variance2.093028029
MonotocityNot monotonic
2020-11-30T23:57:16.350032image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31257429.3%
 
2761117.7%
 
0593613.8%
 
437988.8%
 
528436.6%
 
122385.2%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
0593613.8%
 
122385.2%
 
2761117.7%
 
31257429.3%
 
437988.8%
 
528436.6%
 
ValueCountFrequency (%) 
528436.6%
 
437988.8%
 
31257429.3%
 
2761117.7%
 
122385.2%
 
0593613.8%
 

KBA13_MAZDA
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean3.041771429
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:16.435069image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation0.9986265915
Coefficient of variation (CV)0.3283042842
Kurtosis-0.2685258541
Mean3.041771429
Median Absolute Deviation (MAD)1
Skewness0.05547910151
Sum106462
Variance0.9972550693
MonotocityNot monotonic
2020-11-30T23:57:16.519504image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31523435.5%
 
2742717.3%
 
4727316.9%
 
529376.8%
 
121295.0%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
121295.0%
 
2742717.3%
 
31523435.5%
 
4727316.9%
 
529376.8%
 
ValueCountFrequency (%) 
529376.8%
 
4727316.9%
 
31523435.5%
 
2742717.3%
 
121295.0%
 

KBA13_MERCEDES
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean3.166342857
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:16.612441image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.063480578
Coefficient of variation (CV)0.3358703166
Kurtosis-0.4372742372
Mean3.166342857
Median Absolute Deviation (MAD)1
Skewness-0.05341429534
Sum110822
Variance1.130990939
MonotocityNot monotonic
2020-11-30T23:57:16.697075image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31426633.2%
 
4800118.6%
 
2612714.3%
 
5429010.0%
 
123165.4%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
123165.4%
 
2612714.3%
 
31426633.2%
 
4800118.6%
 
5429010.0%
 
ValueCountFrequency (%) 
5429010.0%
 
4800118.6%
 
31426633.2%
 
2612714.3%
 
123165.4%
 

KBA13_MOTOR
Categorical

MISSING

Distinct4
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Memory size335.8 KiB
3
20750 
2
6724 
4
4441 
1
3085 
ValueCountFrequency (%) 
32075048.3%
 
2672415.7%
 
4444110.3%
 
130857.2%
 
(Missing)796218.5%
 
2020-11-30T23:57:16.804829image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters8
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
.3500027.2%
 
03500027.2%
 
32075016.1%
 
n1592412.4%
 
a79626.2%
 
267245.2%
 
444413.4%
 
130852.4%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number7000054.3%
 
Other Punctuation3500027.2%
 
Lowercase Letter2388618.5%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
03500050.0%
 
32075029.6%
 
267249.6%
 
444416.3%
 
130854.4%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
.35000100.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n1592466.7%
 
a796233.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Common10500081.5%
 
Latin2388618.5%
 

Most frequent Common characters

ValueCountFrequency (%) 
.3500033.3%
 
03500033.3%
 
32075019.8%
 
267246.4%
 
444414.2%
 
130852.9%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n1592466.7%
 
a796233.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII128886100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
.3500027.2%
 
03500027.2%
 
32075016.1%
 
n1592412.4%
 
a79626.2%
 
267245.2%
 
444413.4%
 
130852.4%
 

KBA13_NISSAN
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean2.988171429
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:16.893128image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.027843226
Coefficient of variation (CV)0.3439706359
Kurtosis-0.3441363256
Mean2.988171429
Median Absolute Deviation (MAD)1
Skewness0.07826197646
Sum104586
Variance1.056461698
MonotocityNot monotonic
2020-11-30T23:57:16.981352image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31468234.2%
 
2793518.5%
 
4682915.9%
 
529506.9%
 
126046.1%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
126046.1%
 
2793518.5%
 
31468234.2%
 
4682915.9%
 
529506.9%
 
ValueCountFrequency (%) 
529506.9%
 
4682915.9%
 
31468234.2%
 
2793518.5%
 
126046.1%
 

KBA13_OPEL
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean2.910057143
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:17.073356image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.057598066
Coefficient of variation (CV)0.3634286249
Kurtosis-0.3926554168
Mean2.910057143
Median Absolute Deviation (MAD)1
Skewness0.06754725878
Sum101852
Variance1.118513669
MonotocityNot monotonic
2020-11-30T23:57:17.157907image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31447633.7%
 
2791118.4%
 
4631114.7%
 
135388.2%
 
527646.4%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
135388.2%
 
2791118.4%
 
31447633.7%
 
4631114.7%
 
527646.4%
 
ValueCountFrequency (%) 
527646.4%
 
4631114.7%
 
31447633.7%
 
2791118.4%
 
135388.2%
 

KBA13_PEUGEOT
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean3.087114286
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:17.249599image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.01545795
Coefficient of variation (CV)0.3289343562
Kurtosis-0.2816306854
Mean3.087114286
Median Absolute Deviation (MAD)1
Skewness-0.02155379906
Sum108049
Variance1.031154849
MonotocityNot monotonic
2020-11-30T23:57:17.334682image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31518735.3%
 
4773818.0%
 
2656115.3%
 
532257.5%
 
122895.3%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
122895.3%
 
2656115.3%
 
31518735.3%
 
4773818.0%
 
532257.5%
 
ValueCountFrequency (%) 
532257.5%
 
4773818.0%
 
31518735.3%
 
2656115.3%
 
122895.3%
 

KBA13_RENAULT
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean3.030285714
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:17.427084image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.051407256
Coefficient of variation (CV)0.346966377
Kurtosis-0.3999717951
Mean3.030285714
Median Absolute Deviation (MAD)1
Skewness0.0263487237
Sum106060
Variance1.105457217
MonotocityNot monotonic
2020-11-30T23:57:17.512607image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31448233.7%
 
2728317.0%
 
4716716.7%
 
533287.7%
 
127406.4%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
127406.4%
 
2728317.0%
 
31448233.7%
 
4716716.7%
 
533287.7%
 
ValueCountFrequency (%) 
533287.7%
 
4716716.7%
 
31448233.7%
 
2728317.0%
 
127406.4%
 

KBA13_SEG_GELAENDEWAGEN
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean2.989285714
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:17.606290image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.009186385
Coefficient of variation (CV)0.3376011802
Kurtosis-0.248436528
Mean2.989285714
Median Absolute Deviation (MAD)1
Skewness0.01392186253
Sum104625
Variance1.01845716
MonotocityNot monotonic
2020-11-30T23:57:17.692699image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31541035.9%
 
2726116.9%
 
4697616.2%
 
126996.3%
 
526546.2%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
126996.3%
 
2726116.9%
 
31541035.9%
 
4697616.2%
 
526546.2%
 
ValueCountFrequency (%) 
526546.2%
 
4697616.2%
 
31541035.9%
 
2726116.9%
 
126996.3%
 

KBA13_SEG_GROSSRAUMVANS
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean3.103171429
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:17.785270image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.036002224
Coefficient of variation (CV)0.3338527206
Kurtosis-0.3640327621
Mean3.103171429
Median Absolute Deviation (MAD)1
Skewness-0.002676885608
Sum108611
Variance1.073300608
MonotocityNot monotonic
2020-11-30T23:57:17.870016image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31473634.3%
 
4766717.8%
 
2670615.6%
 
536088.4%
 
122835.3%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
122835.3%
 
2670615.6%
 
31473634.3%
 
4766717.8%
 
536088.4%
 
ValueCountFrequency (%) 
536088.4%
 
4766717.8%
 
31473634.3%
 
2670615.6%
 
122835.3%
 

KBA13_SEG_KLEINST
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean2.940771429
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:17.963341image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.031161377
Coefficient of variation (CV)0.3506431566
Kurtosis-0.3138633653
Mean2.940771429
Median Absolute Deviation (MAD)1
Skewness0.03389759052
Sum102927
Variance1.063293785
MonotocityNot monotonic
2020-11-30T23:57:18.046825image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31501835.0%
 
2759417.7%
 
4660315.4%
 
131637.4%
 
526226.1%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
131637.4%
 
2759417.7%
 
31501835.0%
 
4660315.4%
 
526226.1%
 
ValueCountFrequency (%) 
526226.1%
 
4660315.4%
 
31501835.0%
 
2759417.7%
 
131637.4%
 

KBA13_SEG_KLEINWAGEN
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean2.9282
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:18.137549image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.032910361
Coefficient of variation (CV)0.3527458375
Kurtosis-0.3164924875
Mean2.9282
Median Absolute Deviation (MAD)1
Skewness0.03887010357
Sum102487
Variance1.066903814
MonotocityNot monotonic
2020-11-30T23:57:18.221432image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31500534.9%
 
2765917.8%
 
4649415.1%
 
132587.6%
 
525846.0%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
132587.6%
 
2765917.8%
 
31500534.9%
 
4649415.1%
 
525846.0%
 
ValueCountFrequency (%) 
525846.0%
 
4649415.1%
 
31500534.9%
 
2765917.8%
 
132587.6%
 

KBA13_SEG_KOMPAKTKLASSE
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean2.969085714
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:18.312546image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.029057956
Coefficient of variation (CV)0.346590855
Kurtosis-0.2855323597
Mean2.969085714
Median Absolute Deviation (MAD)1
Skewness0.065560979
Sum103918
Variance1.058960277
MonotocityNot monotonic
2020-11-30T23:57:18.396200image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31523835.5%
 
2755717.6%
 
4642715.0%
 
529016.8%
 
128776.7%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
128776.7%
 
2755717.6%
 
31523835.5%
 
4642715.0%
 
529016.8%
 
ValueCountFrequency (%) 
529016.8%
 
4642715.0%
 
31523835.5%
 
2755717.6%
 
128776.7%
 

KBA13_SEG_MINIVANS
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean3.031628571
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:18.487109image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.004802707
Coefficient of variation (CV)0.331439912
Kurtosis-0.2443722499
Mean3.031628571
Median Absolute Deviation (MAD)1
Skewness0.02408236365
Sum106107
Variance1.00962848
MonotocityNot monotonic
2020-11-30T23:57:18.573354image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31544235.9%
 
4718016.7%
 
2710716.5%
 
528946.7%
 
123775.5%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
123775.5%
 
2710716.5%
 
31544235.9%
 
4718016.7%
 
528946.7%
 
ValueCountFrequency (%) 
528946.7%
 
4718016.7%
 
31544235.9%
 
2710716.5%
 
123775.5%
 

KBA13_SEG_MINIWAGEN
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean3.052342857
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:18.667439image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.014370133
Coefficient of variation (CV)0.332325096
Kurtosis-0.302846658
Mean3.052342857
Median Absolute Deviation (MAD)1
Skewness0.02792554485
Sum106832
Variance1.028946767
MonotocityNot monotonic
2020-11-30T23:57:18.751737image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31505035.0%
 
4739017.2%
 
2717416.7%
 
530977.2%
 
122895.3%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
122895.3%
 
2717416.7%
 
31505035.0%
 
4739017.2%
 
530977.2%
 
ValueCountFrequency (%) 
530977.2%
 
4739017.2%
 
31505035.0%
 
2717416.7%
 
122895.3%
 

KBA13_SEG_MITTELKLASSE
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean3.066485714
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:18.843109image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.022620353
Coefficient of variation (CV)0.333482836
Kurtosis-0.3143259036
Mean3.066485714
Median Absolute Deviation (MAD)1
Skewness0.02347361744
Sum107327
Variance1.045752386
MonotocityNot monotonic
2020-11-30T23:57:18.930299image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31505435.0%
 
4735817.1%
 
2698516.3%
 
532907.7%
 
123135.4%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
123135.4%
 
2698516.3%
 
31505435.0%
 
4735817.1%
 
532907.7%
 
ValueCountFrequency (%) 
532907.7%
 
4735817.1%
 
31505435.0%
 
2698516.3%
 
123135.4%
 

KBA13_SEG_OBEREMITTELKLASSE
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean3.1144
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:19.022376image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.037924023
Coefficient of variation (CV)0.3332661259
Kurtosis-0.3562629347
Mean3.1144
Median Absolute Deviation (MAD)1
Skewness-0.02009616257
Sum109004
Variance1.077286277
MonotocityNot monotonic
2020-11-30T23:57:19.106230image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31479334.4%
 
4774618.0%
 
2647615.1%
 
536768.6%
 
123095.4%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
123095.4%
 
2647615.1%
 
31479334.4%
 
4774618.0%
 
536768.6%
 
ValueCountFrequency (%) 
536768.6%
 
4774618.0%
 
31479334.4%
 
2647615.1%
 
123095.4%
 

KBA13_SEG_OBERKLASSE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean2.477914286
Minimum0
Maximum5
Zeros3823
Zeros (%)8.9%
Memory size335.8 KiB
2020-11-30T23:57:19.193004image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median3
Q33
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.480589843
Coefficient of variation (CV)0.5975145514
Kurtosis-0.8957732887
Mean2.477914286
Median Absolute Deviation (MAD)1
Skewness-0.04962140726
Sum86727
Variance2.192146283
MonotocityNot monotonic
2020-11-30T23:57:19.275509image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31237528.8%
 
1723916.8%
 
439509.2%
 
238348.9%
 
038238.9%
 
537798.8%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
038238.9%
 
1723916.8%
 
238348.9%
 
31237528.8%
 
439509.2%
 
537798.8%
 
ValueCountFrequency (%) 
537798.8%
 
439509.2%
 
31237528.8%
 
238348.9%
 
1723916.8%
 
038238.9%
 

KBA13_SEG_SONSTIGE
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean3.044028571
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:19.358679image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation0.9509702762
Coefficient of variation (CV)0.3124051742
Kurtosis-0.1414160127
Mean3.044028571
Median Absolute Deviation (MAD)1
Skewness0.09859089208
Sum106541
Variance0.9043444662
MonotocityNot monotonic
2020-11-30T23:57:19.457239image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31602837.3%
 
2752617.5%
 
4719716.8%
 
525926.0%
 
116573.9%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
116573.9%
 
2752617.5%
 
31602837.3%
 
4719716.8%
 
525926.0%
 
ValueCountFrequency (%) 
525926.0%
 
4719716.8%
 
31602837.3%
 
2752617.5%
 
116573.9%
 

KBA13_SEG_SPORTWAGEN
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean2.574571429
Minimum0
Maximum5
Zeros3526
Zeros (%)8.2%
Memory size335.8 KiB
2020-11-30T23:57:19.566530image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median3
Q33
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.44336365
Coefficient of variation (CV)0.5606228802
Kurtosis-0.7164490729
Mean2.574571429
Median Absolute Deviation (MAD)1
Skewness-0.09286666306
Sum90110
Variance2.083298625
MonotocityNot monotonic
2020-11-30T23:57:19.653626image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31163227.1%
 
2646315.0%
 
1511311.9%
 
441559.7%
 
541119.6%
 
035268.2%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
035268.2%
 
1511311.9%
 
2646315.0%
 
31163227.1%
 
441559.7%
 
541119.6%
 
ValueCountFrequency (%) 
541119.6%
 
441559.7%
 
31163227.1%
 
2646315.0%
 
1511311.9%
 
035268.2%
 

KBA13_SEG_UTILITIES
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean3.011857143
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:19.736877image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.002070477
Coefficient of variation (CV)0.3327085016
Kurtosis-0.242816463
Mean3.011857143
Median Absolute Deviation (MAD)1
Skewness0.02790916484
Sum105415
Variance1.004145241
MonotocityNot monotonic
2020-11-30T23:57:19.822908image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31540635.9%
 
2730017.0%
 
4710916.5%
 
527446.4%
 
124415.7%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
124415.7%
 
2730017.0%
 
31540635.9%
 
4710916.5%
 
527446.4%
 
ValueCountFrequency (%) 
527446.4%
 
4710916.5%
 
31540635.9%
 
2730017.0%
 
124415.7%
 

KBA13_SEG_VAN
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean3.072942857
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:19.921356image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.012885593
Coefficient of variation (CV)0.3296141971
Kurtosis-0.2764340065
Mean3.072942857
Median Absolute Deviation (MAD)1
Skewness0.01116351185
Sum107553
Variance1.025937224
MonotocityNot monotonic
2020-11-30T23:57:20.007916image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31528135.6%
 
4745317.3%
 
2680815.8%
 
532067.5%
 
122525.2%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
122525.2%
 
2680815.8%
 
31528135.6%
 
4745317.3%
 
532067.5%
 
ValueCountFrequency (%) 
532067.5%
 
4745317.3%
 
31528135.6%
 
2680815.8%
 
122525.2%
 

KBA13_SEG_WOHNMOBILE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean2.486457143
Minimum0
Maximum5
Zeros3870
Zeros (%)9.0%
Memory size335.8 KiB
2020-11-30T23:57:20.096803image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median3
Q33
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.406348448
Coefficient of variation (CV)0.5656033333
Kurtosis-0.616022627
Mean2.486457143
Median Absolute Deviation (MAD)1
Skewness-0.07861841807
Sum87026
Variance1.977815957
MonotocityNot monotonic
2020-11-30T23:57:20.180127image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31174827.3%
 
2746917.4%
 
1472211.0%
 
038709.0%
 
438338.9%
 
533587.8%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
038709.0%
 
1472211.0%
 
2746917.4%
 
31174827.3%
 
438338.9%
 
533587.8%
 
ValueCountFrequency (%) 
533587.8%
 
438338.9%
 
31174827.3%
 
2746917.4%
 
1472211.0%
 
038709.0%
 

KBA13_SITZE_4
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean3.138971429
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:20.263369image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.081205834
Coefficient of variation (CV)0.3444458986
Kurtosis-0.4983697373
Mean3.138971429
Median Absolute Deviation (MAD)1
Skewness-0.04610907686
Sum109864
Variance1.169006056
MonotocityNot monotonic
2020-11-30T23:57:20.348046image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31382832.2%
 
4790718.4%
 
2645915.0%
 
542579.9%
 
125495.9%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
125495.9%
 
2645915.0%
 
31382832.2%
 
4790718.4%
 
542579.9%
 
ValueCountFrequency (%) 
542579.9%
 
4790718.4%
 
31382832.2%
 
2645915.0%
 
125495.9%
 

KBA13_SITZE_5
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean2.843057143
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:20.443862image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.100598853
Coefficient of variation (CV)0.3871180906
Kurtosis-0.5471161074
Mean2.843057143
Median Absolute Deviation (MAD)1
Skewness0.09115509314
Sum99507
Variance1.211317834
MonotocityNot monotonic
2020-11-30T23:57:20.531942image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31332231.0%
 
2826419.2%
 
4622114.5%
 
1445910.4%
 
527346.4%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
1445910.4%
 
2826419.2%
 
31332231.0%
 
4622114.5%
 
527346.4%
 
ValueCountFrequency (%) 
527346.4%
 
4622114.5%
 
31332231.0%
 
2826419.2%
 
1445910.4%
 

KBA13_SITZE_6
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean3.102971429
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:20.629547image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.074457277
Coefficient of variation (CV)0.3462672158
Kurtosis-0.4513199155
Mean3.102971429
Median Absolute Deviation (MAD)1
Skewness-0.05901431914
Sum108604
Variance1.154458441
MonotocityNot monotonic
2020-11-30T23:57:20.719532image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31412932.9%
 
4786118.3%
 
2637514.8%
 
538479.0%
 
127886.5%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
127886.5%
 
2637514.8%
 
31412932.9%
 
4786118.3%
 
538479.0%
 
ValueCountFrequency (%) 
538479.0%
 
4786118.3%
 
31412932.9%
 
2637514.8%
 
127886.5%
 

KBA13_TOYOTA
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean3.080342857
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:20.818188image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.032350185
Coefficient of variation (CV)0.3351413244
Kurtosis-0.357755812
Mean3.080342857
Median Absolute Deviation (MAD)1
Skewness0.03135901925
Sum107812
Variance1.065746904
MonotocityNot monotonic
2020-11-30T23:57:20.909958image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31480834.5%
 
4737917.2%
 
2703516.4%
 
535068.2%
 
122725.3%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
122725.3%
 
2703516.4%
 
31480834.5%
 
4737917.2%
 
535068.2%
 
ValueCountFrequency (%) 
535068.2%
 
4737917.2%
 
31480834.5%
 
2703516.4%
 
122725.3%
 

KBA13_VORB_0
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean3.236514286
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:21.007923image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9769791522
Coefficient of variation (CV)0.3018615294
Kurtosis-0.2610934992
Mean3.236514286
Median Absolute Deviation (MAD)1
Skewness0.0005470347358
Sum113278
Variance0.9544882637
MonotocityNot monotonic
2020-11-30T23:57:21.100774image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31546136.0%
 
4862020.1%
 
2564413.1%
 
539639.2%
 
113123.1%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
113123.1%
 
2564413.1%
 
31546136.0%
 
4862020.1%
 
539639.2%
 
ValueCountFrequency (%) 
539639.2%
 
4862020.1%
 
31546136.0%
 
2564413.1%
 
113123.1%
 

KBA13_VORB_1
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean3.047428571
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:21.202935image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation0.9577083627
Coefficient of variation (CV)0.3142676982
Kurtosis-0.1217178573
Mean3.047428571
Median Absolute Deviation (MAD)1
Skewness0.01010718229
Sum106660
Variance0.9172053079
MonotocityNot monotonic
2020-11-30T23:57:21.294335image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31608337.4%
 
4754117.6%
 
2695516.2%
 
524795.8%
 
119424.5%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
119424.5%
 
2695516.2%
 
31608337.4%
 
4754117.6%
 
524795.8%
 
ValueCountFrequency (%) 
524795.8%
 
4754117.6%
 
31608337.4%
 
2695516.2%
 
119424.5%
 

KBA13_VORB_1_2
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean2.925685714
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:21.390271image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation0.9796889934
Coefficient of variation (CV)0.3348579065
Kurtosis-0.1873345553
Mean2.925685714
Median Absolute Deviation (MAD)1
Skewness-0.01256867337
Sum102399
Variance0.9597905238
MonotocityNot monotonic
2020-11-30T23:57:24.592356image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31574736.7%
 
2761917.7%
 
4679015.8%
 
128656.7%
 
519794.6%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
128656.7%
 
2761917.7%
 
31574736.7%
 
4679015.8%
 
519794.6%
 
ValueCountFrequency (%) 
519794.6%
 
4679015.8%
 
31574736.7%
 
2761917.7%
 
128656.7%
 

KBA13_VORB_2
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean2.941285714
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:24.685836image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q33
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.949093446
Coefficient of variation (CV)0.3226797864
Kurtosis-0.1129413671
Mean2.941285714
Median Absolute Deviation (MAD)1
Skewness0.05438632145
Sum102945
Variance0.9007783692
MonotocityNot monotonic
2020-11-30T23:57:24.772100image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31600437.3%
 
2810418.9%
 
4667515.5%
 
122655.3%
 
519524.5%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
122655.3%
 
2810418.9%
 
31600437.3%
 
4667515.5%
 
519524.5%
 
ValueCountFrequency (%) 
519524.5%
 
4667515.5%
 
31600437.3%
 
2810418.9%
 
122655.3%
 

KBA13_VORB_3
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean2.152171429
Minimum0
Maximum5
Zeros7228
Zeros (%)16.8%
Memory size335.8 KiB
2020-11-30T23:57:24.861547image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q33
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.424655995
Coefficient of variation (CV)0.6619621355
Kurtosis-0.737749626
Mean2.152171429
Median Absolute Deviation (MAD)1
Skewness-0.07006311434
Sum75326
Variance2.029644703
MonotocityNot monotonic
2020-11-30T23:57:24.946405image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31113825.9%
 
2890220.7%
 
0722816.8%
 
129146.8%
 
428966.7%
 
519224.5%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
0722816.8%
 
129146.8%
 
2890220.7%
 
31113825.9%
 
428966.7%
 
519224.5%
 
ValueCountFrequency (%) 
519224.5%
 
428966.7%
 
31113825.9%
 
2890220.7%
 
129146.8%
 
0722816.8%
 

KBA13_VW
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7962
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean2.961571429
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:25.030221image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.01573823
Coefficient of variation (CV)0.3429727272
Kurtosis-0.2517372098
Mean2.961571429
Median Absolute Deviation (MAD)1
Skewness0.00801281858
Sum103655
Variance1.031724151
MonotocityNot monotonic
2020-11-30T23:57:25.116090image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31546236.0%
 
2725016.9%
 
4674715.7%
 
129816.9%
 
525606.0%
 
(Missing)796218.5%
 
ValueCountFrequency (%) 
129816.9%
 
2725016.9%
 
31546236.0%
 
4674715.7%
 
525606.0%
 
ValueCountFrequency (%) 
525606.0%
 
4674715.7%
 
31546236.0%
 
2725016.9%
 
129816.9%
 

KK_KUNDENTYP
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing25316
Missing (%)58.9%
Infinite0
Infinite (%)0.0%
Mean3.41533492
Minimum1
Maximum6
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:25.204824image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q35
95-th percentile6
Maximum6
Range5
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.650214621
Coefficient of variation (CV)0.483177978
Kurtosis-1.185048835
Mean3.41533492
Median Absolute Deviation (MAD)1
Skewness0.1064877933
Sum60267
Variance2.723208295
MonotocityNot monotonic
2020-11-30T23:57:25.296994image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
336188.4%
 
232807.6%
 
528326.6%
 
126976.3%
 
426596.2%
 
625606.0%
 
(Missing)2531658.9%
 
ValueCountFrequency (%) 
126976.3%
 
232807.6%
 
336188.4%
 
426596.2%
 
528326.6%
 
625606.0%
 
ValueCountFrequency (%) 
625606.0%
 
528326.6%
 
426596.2%
 
336188.4%
 
232807.6%
 
126976.3%
 

KKK
Real number (ℝ≥0)

MISSING
ZEROS

Distinct5
Distinct (%)< 0.1%
Missing8445
Missing (%)19.7%
Infinite0
Infinite (%)0.0%
Mean2.536489266
Minimum0
Maximum4
Zeros1485
Zeros (%)3.5%
Memory size335.8 KiB
2020-11-30T23:57:25.383907image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median3
Q33
95-th percentile4
Maximum4
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.108303814
Coefficient of variation (CV)0.436944019
Kurtosis-0.6016780892
Mean2.536489266
Median Absolute Deviation (MAD)1
Skewness-0.4226533238
Sum87552
Variance1.228337344
MonotocityNot monotonic
2020-11-30T23:57:25.465762image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31189027.7%
 
2869020.2%
 
4735017.1%
 
1510211.9%
 
014853.5%
 
(Missing)844519.7%
 
ValueCountFrequency (%) 
014853.5%
 
1510211.9%
 
2869020.2%
 
31189027.7%
 
4735017.1%
 
ValueCountFrequency (%) 
4735017.1%
 
31189027.7%
 
2869020.2%
 
1510211.9%
 
014853.5%
 

KOMBIALTER
Real number (ℝ≥0)

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.576183604
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:25.554213image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q14
median4
Q34
95-th percentile9
Maximum9
Range8
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.040037959
Coefficient of variation (CV)0.4457946042
Kurtosis0.891358381
Mean4.576183604
Median Absolute Deviation (MAD)0
Skewness1.458843781
Sum196602
Variance4.161754872
MonotocityNot monotonic
2020-11-30T23:57:25.635408image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
42793565.0%
 
9705416.4%
 
3598213.9%
 
214393.3%
 
15521.3%
 
ValueCountFrequency (%) 
15521.3%
 
214393.3%
 
3598213.9%
 
42793565.0%
 
9705416.4%
 
ValueCountFrequency (%) 
9705416.4%
 
42793565.0%
 
3598213.9%
 
214393.3%
 
15521.3%
 

KONSUMNAEHE
Real number (ℝ≥0)

MISSING

Distinct7
Distinct (%)< 0.1%
Missing6997
Missing (%)16.3%
Infinite0
Infinite (%)0.0%
Mean3.151258168
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:25.723832image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum7
Range6
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.510438557
Coefficient of variation (CV)0.4793128575
Kurtosis-1.061247479
Mean3.151258168
Median Absolute Deviation (MAD)1
Skewness0.07749730677
Sum113335
Variance2.281424635
MonotocityNot monotonic
2020-11-30T23:57:25.802397image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
3808818.8%
 
5739017.2%
 
1691216.1%
 
4620614.4%
 
2599714.0%
 
612132.8%
 
71590.4%
 
(Missing)699716.3%
 
ValueCountFrequency (%) 
1691216.1%
 
2599714.0%
 
3808818.8%
 
4620614.4%
 
5739017.2%
 
612132.8%
 
71590.4%
 
ValueCountFrequency (%) 
71590.4%
 
612132.8%
 
5739017.2%
 
4620614.4%
 
3808818.8%
 
2599714.0%
 
1691216.1%
 

KONSUMZELLE
Boolean

MISSING

Distinct2
Distinct (%)< 0.1%
Missing7777
Missing (%)18.1%
Memory size335.8 KiB
0
28436 
1
6749 
(Missing)
7777 
ValueCountFrequency (%) 
02843666.2%
 
1674915.7%
 
(Missing)777718.1%
 

LP_FAMILIE_FEIN
Real number (ℝ≥0)

MISSING
ZEROS

Distinct12
Distinct (%)< 0.1%
Missing605
Missing (%)1.4%
Infinite0
Infinite (%)0.0%
Mean4.109403404
Minimum0
Maximum11
Zeros8208
Zeros (%)19.1%
Memory size335.8 KiB
2020-11-30T23:57:25.894469image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q310
95-th percentile11
Maximum11
Range11
Interquartile range (IQR)9

Descriptive statistics

Standard deviation4.392075301
Coefficient of variation (CV)1.068786602
Kurtosis-1.467511144
Mean4.109403404
Median Absolute Deviation (MAD)2
Skewness0.6328992055
Sum174062
Variance19.29032545
MonotocityNot monotonic
2020-11-30T23:57:26.025723image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%) 
11222828.5%
 
10857720.0%
 
0820819.1%
 
2709316.5%
 
11430310.0%
 
86001.4%
 
95901.4%
 
73770.9%
 
51710.4%
 
41190.3%
 
6640.1%
 
3270.1%
 
(Missing)6051.4%
 
ValueCountFrequency (%) 
0820819.1%
 
11222828.5%
 
2709316.5%
 
3270.1%
 
41190.3%
 
51710.4%
 
6640.1%
 
73770.9%
 
86001.4%
 
95901.4%
 
ValueCountFrequency (%) 
11430310.0%
 
10857720.0%
 
95901.4%
 
86001.4%
 
73770.9%
 
6640.1%
 
51710.4%
 
41190.3%
 
3270.1%
 
2709316.5%
 

LP_FAMILIE_GROB
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing605
Missing (%)1.4%
Infinite0
Infinite (%)0.0%
Mean2.33441934
Minimum0
Maximum5
Zeros8208
Zeros (%)19.1%
Memory size335.8 KiB
2020-11-30T23:57:26.125480image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q35
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)4

Descriptive statistics

Standard deviation1.979889627
Coefficient of variation (CV)0.8481293796
Kurtosis-1.508513307
Mean2.33441934
Median Absolute Deviation (MAD)2
Skewness0.3841764798
Sum98879
Variance3.919962934
MonotocityNot monotonic
2020-11-30T23:57:26.225256image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
51347031.4%
 
11222828.5%
 
0820819.1%
 
2709316.5%
 
410412.4%
 
33170.7%
 
(Missing)6051.4%
 
ValueCountFrequency (%) 
0820819.1%
 
11222828.5%
 
2709316.5%
 
33170.7%
 
410412.4%
 
51347031.4%
 
ValueCountFrequency (%) 
51347031.4%
 
410412.4%
 
33170.7%
 
2709316.5%
 
11222828.5%
 
0820819.1%
 

LP_LEBENSPHASE_FEIN
Real number (ℝ≥0)

MISSING
ZEROS

Distinct41
Distinct (%)0.1%
Missing605
Missing (%)1.4%
Infinite0
Infinite (%)0.0%
Mean17.66107137
Minimum0
Maximum40
Zeros8298
Zeros (%)19.3%
Memory size335.8 KiB
2020-11-30T23:57:26.338425image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q16
median15
Q332
95-th percentile40
Maximum40
Range40
Interquartile range (IQR)26

Descriptive statistics

Standard deviation14.08570151
Coefficient of variation (CV)0.797556457
Kurtosis-1.364828806
Mean17.66107137
Median Absolute Deviation (MAD)15
Skewness0.2793471299
Sum748070
Variance198.406987
MonotocityNot monotonic
2020-11-30T23:57:26.477864image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%) 
0829819.3%
 
630677.1%
 
4024685.7%
 
824165.6%
 
3820764.8%
 
1320614.8%
 
1219204.5%
 
2018544.3%
 
3116663.9%
 
3216333.8%
 
1915773.7%
 
1515043.5%
 
3614403.4%
 
1613233.1%
 
3912552.9%
 
3711912.8%
 
56901.6%
 
96531.5%
 
176481.5%
 
355221.2%
 
114331.0%
 
73920.9%
 
283740.9%
 
303710.9%
 
343440.8%
 
Other values (16)21815.1%
 
(Missing)6051.4%
 
ValueCountFrequency (%) 
0829819.3%
 
11310.3%
 
21240.3%
 
3750.2%
 
4780.2%
 
56901.6%
 
630677.1%
 
73920.9%
 
824165.6%
 
96531.5%
 
ValueCountFrequency (%) 
4024685.7%
 
3912552.9%
 
3820764.8%
 
3711912.8%
 
3614403.4%
 
355221.2%
 
343440.8%
 
332430.6%
 
3216333.8%
 
3116663.9%
 

LP_LEBENSPHASE_GROB
Real number (ℝ≥0)

MISSING
ZEROS

Distinct13
Distinct (%)< 0.1%
Missing605
Missing (%)1.4%
Infinite0
Infinite (%)0.0%
Mean5.274995868
Minimum0
Maximum12
Zeros8273
Zeros (%)19.3%
Memory size335.8 KiB
2020-11-30T23:57:26.627841image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median4
Q310
95-th percentile12
Maximum12
Range12
Interquartile range (IQR)8

Descriptive statistics

Standard deviation4.470538304
Coefficient of variation (CV)0.8474960768
Kurtosis-1.36366669
Mean5.274995868
Median Absolute Deviation (MAD)4
Skewness0.4290829214
Sum223433
Variance19.98571272
MonotocityNot monotonic
2020-11-30T23:57:26.745782image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%) 
12843019.6%
 
0827319.3%
 
2656515.3%
 
3522512.2%
 
541509.7%
 
1032997.7%
 
429436.9%
 
1111092.6%
 
87871.8%
 
95971.4%
 
14080.9%
 
63170.7%
 
72540.6%
 
(Missing)6051.4%
 
ValueCountFrequency (%) 
0827319.3%
 
14080.9%
 
2656515.3%
 
3522512.2%
 
429436.9%
 
541509.7%
 
63170.7%
 
72540.6%
 
87871.8%
 
95971.4%
 
ValueCountFrequency (%) 
12843019.6%
 
1111092.6%
 
1032997.7%
 
95971.4%
 
87871.8%
 
72540.6%
 
63170.7%
 
541509.7%
 
429436.9%
 
3522512.2%
 

LP_STATUS_FEIN
Real number (ℝ≥0)

MISSING

Distinct10
Distinct (%)< 0.1%
Missing605
Missing (%)1.4%
Infinite0
Infinite (%)0.0%
Mean5.92700144
Minimum1
Maximum10
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:26.864486image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median5
Q39
95-th percentile10
Maximum10
Range9
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.39833627
Coefficient of variation (CV)0.5733651838
Kurtosis-1.491594681
Mean5.92700144
Median Absolute Deviation (MAD)4
Skewness-0.1591674838
Sum251050
Variance11.54868941
MonotocityNot monotonic
2020-11-30T23:57:27.000892image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
10913121.3%
 
9847919.7%
 
1808718.8%
 
5611414.2%
 
341999.8%
 
425375.9%
 
618984.4%
 
712432.9%
 
25691.3%
 
81000.2%
 
(Missing)6051.4%
 
ValueCountFrequency (%) 
1808718.8%
 
25691.3%
 
341999.8%
 
425375.9%
 
5611414.2%
 
618984.4%
 
712432.9%
 
81000.2%
 
9847919.7%
 
10913121.3%
 
ValueCountFrequency (%) 
10913121.3%
 
9847919.7%
 
81000.2%
 
712432.9%
 
618984.4%
 
5611414.2%
 
425375.9%
 
341999.8%
 
25691.3%
 
1808718.8%
 

LP_STATUS_GROB
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing605
Missing (%)1.4%
Infinite0
Infinite (%)0.0%
Mean2.921595014
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:27.102807image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median2
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.476326688
Coefficient of variation (CV)0.5053153094
Kurtosis-1.462862029
Mean2.921595014
Median Absolute Deviation (MAD)1
Skewness0.1560257459
Sum123750
Variance2.179540491
MonotocityNot monotonic
2020-11-30T23:57:27.204592image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
21285029.9%
 
5913121.3%
 
1865620.1%
 
4857920.0%
 
331417.3%
 
(Missing)6051.4%
 
ValueCountFrequency (%) 
1865620.1%
 
21285029.9%
 
331417.3%
 
4857920.0%
 
5913121.3%
 
ValueCountFrequency (%) 
5913121.3%
 
4857920.0%
 
331417.3%
 
21285029.9%
 
1865620.1%
 

MIN_GEBAEUDEJAHR
Real number (ℝ≥0)

MISSING

Distinct31
Distinct (%)0.1%
Missing7777
Missing (%)18.1%
Infinite0
Infinite (%)0.0%
Mean1992.855848
Minimum1985
Maximum2015
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:27.324835image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1985
5-th percentile1992
Q11992
median1992
Q31992
95-th percentile1997
Maximum2015
Range30
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.456724464
Coefficient of variation (CV)0.001232765765
Kurtosis22.94704159
Mean1992.855848
Median Absolute Deviation (MAD)0
Skewness4.204989958
Sum70118633
Variance6.035495093
MonotocityNot monotonic
2020-11-30T23:57:27.443836image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%) 
19922584060.1%
 
199437458.7%
 
199312703.0%
 
19959412.2%
 
19966681.6%
 
19975781.3%
 
19913250.8%
 
19902810.7%
 
20002510.6%
 
20011590.4%
 
20051310.3%
 
19981200.3%
 
19891160.3%
 
20021080.3%
 
19991050.2%
 
2004810.2%
 
2003770.2%
 
2007510.1%
 
1988490.1%
 
2006450.1%
 
2008390.1%
 
2009340.1%
 
2012320.1%
 
1987310.1%
 
2011270.1%
 
Other values (6)810.2%
 
(Missing)777718.1%
 
ValueCountFrequency (%) 
19855< 0.1%
 
19868< 0.1%
 
1987310.1%
 
1988490.1%
 
19891160.3%
 
19902810.7%
 
19913250.8%
 
19922584060.1%
 
199312703.0%
 
199437458.7%
 
ValueCountFrequency (%) 
20159< 0.1%
 
201417< 0.1%
 
201318< 0.1%
 
2012320.1%
 
2011270.1%
 
2010240.1%
 
2009340.1%
 
2008390.1%
 
2007510.1%
 
2006450.1%
 

MOBI_RASTER
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing7777
Missing (%)18.1%
Infinite0
Infinite (%)0.0%
Mean2.691942589
Minimum1
Maximum6
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:27.552890image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median3
Q34
95-th percentile5
Maximum6
Range5
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.600008222
Coefficient of variation (CV)0.5943693705
Kurtosis-1.089556315
Mean2.691942589
Median Absolute Deviation (MAD)2
Skewness0.4437766103
Sum94716
Variance2.560026311
MonotocityNot monotonic
2020-11-30T23:57:27.653192image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
11255929.2%
 
3614814.3%
 
4515012.0%
 
2502911.7%
 
5473911.0%
 
615603.6%
 
(Missing)777718.1%
 
ValueCountFrequency (%) 
11255929.2%
 
2502911.7%
 
3614814.3%
 
4515012.0%
 
5473911.0%
 
615603.6%
 
ValueCountFrequency (%) 
615603.6%
 
5473911.0%
 
4515012.0%
 
3614814.3%
 
2502911.7%
 
11255929.2%
 

MOBI_REGIO
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing8648
Missing (%)20.1%
Infinite0
Infinite (%)0.0%
Mean3.328612228
Minimum1
Maximum6
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:27.750408image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median4
Q35
95-th percentile5
Maximum6
Range5
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.414178205
Coefficient of variation (CV)0.4248551972
Kurtosis-1.181409417
Mean3.328612228
Median Absolute Deviation (MAD)1
Skewness-0.3423400394
Sum114218
Variance1.999899995
MonotocityNot monotonic
2020-11-30T23:57:27.847302image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
5935121.8%
 
4823019.2%
 
3636614.8%
 
1538112.5%
 
2496311.6%
 
6230.1%
 
(Missing)864820.1%
 
ValueCountFrequency (%) 
1538112.5%
 
2496311.6%
 
3636614.8%
 
4823019.2%
 
5935121.8%
 
6230.1%
 
ValueCountFrequency (%) 
6230.1%
 
5935121.8%
 
4823019.2%
 
3636614.8%
 
2496311.6%
 
1538112.5%
 

NATIONALITAET_KZ
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size335.8 KiB
1
34424 
0
7316 
2
 
720
3
 
502
ValueCountFrequency (%) 
13442480.1%
 
0731617.0%
 
27201.7%
 
35021.2%
 
2020-11-30T23:57:27.966638image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters4
Unique unicode categories1 ?
Unique unicode scripts1 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
13442480.1%
 
0731617.0%
 
27201.7%
 
35021.2%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number42962100.0%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
13442480.1%
 
0731617.0%
 
27201.7%
 
35021.2%
 

Most occurring scripts

ValueCountFrequency (%) 
Common42962100.0%
 

Most frequent Common characters

ValueCountFrequency (%) 
13442480.1%
 
0731617.0%
 
27201.7%
 
35021.2%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII42962100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
13442480.1%
 
0731617.0%
 
27201.7%
 
35021.2%
 

ONLINE_AFFINITAET
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing605
Missing (%)1.4%
Infinite0
Infinite (%)0.0%
Mean2.57985693
Minimum0
Maximum5
Zeros2156
Zeros (%)5.0%
Memory size335.8 KiB
2020-11-30T23:57:28.065404image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median2
Q34
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.360915219
Coefficient of variation (CV)0.5275157715
Kurtosis-0.8402103647
Mean2.57985693
Median Absolute Deviation (MAD)1
Skewness0.1488308148
Sum109275
Variance1.852090234
MonotocityNot monotonic
2020-11-30T23:57:28.167931image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
21443733.6%
 
4863920.1%
 
1681315.9%
 
3626414.6%
 
540489.4%
 
021565.0%
 
(Missing)6051.4%
 
ValueCountFrequency (%) 
021565.0%
 
1681315.9%
 
21443733.6%
 
3626414.6%
 
4863920.1%
 
540489.4%
 
ValueCountFrequency (%) 
540489.4%
 
4863920.1%
 
3626414.6%
 
21443733.6%
 
1681315.9%
 
021565.0%
 

ORTSGR_KLS9
Real number (ℝ≥0)

MISSING

Distinct10
Distinct (%)< 0.1%
Missing7951
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean5.152352118
Minimum0
Maximum9
Zeros4
Zeros (%)< 0.1%
Memory size335.8 KiB
2020-11-30T23:57:28.271855image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q13
median5
Q37
95-th percentile9
Maximum9
Range9
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.387266
Coefficient of variation (CV)0.4633351808
Kurtosis-1.032735019
Mean5.152352118
Median Absolute Deviation (MAD)2
Skewness0.1326188369
Sum180389
Variance5.699038955
MonotocityNot monotonic
2020-11-30T23:57:28.365504image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
5622914.5%
 
4533612.4%
 
9462610.8%
 
3431510.0%
 
736258.4%
 
234978.1%
 
828796.7%
 
626846.2%
 
118164.2%
 
04< 0.1%
 
(Missing)795118.5%
 
ValueCountFrequency (%) 
04< 0.1%
 
118164.2%
 
234978.1%
 
3431510.0%
 
4533612.4%
 
5622914.5%
 
626846.2%
 
736258.4%
 
828796.7%
 
9462610.8%
 
ValueCountFrequency (%) 
9462610.8%
 
828796.7%
 
736258.4%
 
626846.2%
 
5622914.5%
 
4533612.4%
 
3431510.0%
 
234978.1%
 
118164.2%
 
04< 0.1%
 

OST_WEST_KZ
Categorical

MISSING

Distinct2
Distinct (%)< 0.1%
Missing7777
Missing (%)18.1%
Memory size335.8 KiB
W
26752 
O
8433 
ValueCountFrequency (%) 
W2675262.3%
 
O843319.6%
 
(Missing)777718.1%
 
2020-11-30T23:57:28.480307image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters4
Unique unicode categories2 ?
Unique unicode scripts1 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
W2675245.7%
 
n1555426.6%
 
O843314.4%
 
a777713.3%
 

Most occurring categories

ValueCountFrequency (%) 
Uppercase Letter3518560.1%
 
Lowercase Letter2333139.9%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
W2675276.0%
 
O843324.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n1555466.7%
 
a777733.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin58516100.0%
 

Most frequent Latin characters

ValueCountFrequency (%) 
W2675245.7%
 
n1555426.6%
 
O843314.4%
 
a777713.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII58516100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
W2675245.7%
 
n1555426.6%
 
O843314.4%
 
a777713.3%
 

PLZ8_ANTG1
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing8153
Missing (%)19.0%
Infinite0
Infinite (%)0.0%
Mean2.388951133
Minimum0
Maximum4
Zeros229
Zeros (%)0.5%
Memory size335.8 KiB
2020-11-30T23:57:28.586156image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median2
Q33
95-th percentile4
Maximum4
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.976407967
Coefficient of variation (CV)0.4087182669
Kurtosis-0.8539688415
Mean2.388951133
Median Absolute Deviation (MAD)1
Skewness0.02786278464
Sum83157
Variance0.953372518
MonotocityNot monotonic
2020-11-30T23:57:28.684838image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
21179927.5%
 
31101225.6%
 
1685115.9%
 
4491811.4%
 
02290.5%
 
(Missing)815319.0%
 
ValueCountFrequency (%) 
02290.5%
 
1685115.9%
 
21179927.5%
 
31101225.6%
 
4491811.4%
 
ValueCountFrequency (%) 
4491811.4%
 
31101225.6%
 
21179927.5%
 
1685115.9%
 
02290.5%
 

PLZ8_ANTG2
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing8153
Missing (%)19.0%
Infinite0
Infinite (%)0.0%
Mean2.710965555
Minimum0
Maximum4
Zeros369
Zeros (%)0.9%
Memory size335.8 KiB
2020-11-30T23:57:28.794144image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median3
Q33
95-th percentile4
Maximum4
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9259999975
Coefficient of variation (CV)0.3415757149
Kurtosis-0.3427473785
Mean2.710965555
Median Absolute Deviation (MAD)1
Skewness-0.3548187874
Sum94366
Variance0.8574759954
MonotocityNot monotonic
2020-11-30T23:57:28.895337image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31381132.1%
 
21038924.2%
 
4730517.0%
 
129356.8%
 
03690.9%
 
(Missing)815319.0%
 
ValueCountFrequency (%) 
03690.9%
 
129356.8%
 
21038924.2%
 
31381132.1%
 
4730517.0%
 
ValueCountFrequency (%) 
4730517.0%
 
31381132.1%
 
21038924.2%
 
129356.8%
 
03690.9%
 

PLZ8_ANTG3
Categorical

MISSING

Distinct4
Distinct (%)< 0.1%
Missing8153
Missing (%)19.0%
Memory size335.8 KiB
1
11608 
2
10653 
0
6481 
3
6067 
ValueCountFrequency (%) 
11160827.0%
 
21065324.8%
 
0648115.1%
 
3606714.1%
 
(Missing)815319.0%
 
2020-11-30T23:57:29.030174image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters7
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
04129032.0%
 
.3480927.0%
 
n1630612.7%
 
1116089.0%
 
2106538.3%
 
a81536.3%
 
360674.7%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number6961854.0%
 
Other Punctuation3480927.0%
 
Lowercase Letter2445919.0%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
04129059.3%
 
11160816.7%
 
21065315.3%
 
360678.7%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
.34809100.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n1630666.7%
 
a815333.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Common10442781.0%
 
Latin2445919.0%
 

Most frequent Common characters

ValueCountFrequency (%) 
04129039.5%
 
.3480933.3%
 
11160811.1%
 
21065310.2%
 
360675.8%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n1630666.7%
 
a815333.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII128886100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
04129032.0%
 
.3480927.0%
 
n1630612.7%
 
1116089.0%
 
2106538.3%
 
a81536.3%
 
360674.7%
 

PLZ8_ANTG4
Categorical

MISSING

Distinct3
Distinct (%)< 0.1%
Missing8153
Missing (%)19.0%
Memory size335.8 KiB
0
17981 
1
12259 
2
4569 
ValueCountFrequency (%) 
01798141.9%
 
11225928.5%
 
2456910.6%
 
(Missing)815319.0%
 
2020-11-30T23:57:29.151774image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters6
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
05279041.0%
 
.3480927.0%
 
n1630612.7%
 
1122599.5%
 
a81536.3%
 
245693.5%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number6961854.0%
 
Other Punctuation3480927.0%
 
Lowercase Letter2445919.0%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
05279075.8%
 
11225917.6%
 
245696.6%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
.34809100.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n1630666.7%
 
a815333.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Common10442781.0%
 
Latin2445919.0%
 

Most frequent Common characters

ValueCountFrequency (%) 
05279050.6%
 
.3480933.3%
 
11225911.7%
 
245694.4%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n1630666.7%
 
a815333.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII128886100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
05279041.0%
 
.3480927.0%
 
n1630612.7%
 
1122599.5%
 
a81536.3%
 
245693.5%
 

PLZ8_BAUMAX
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing8153
Missing (%)19.0%
Infinite0
Infinite (%)0.0%
Mean1.777787354
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:29.258435image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q32
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.360034943
Coefficient of variation (CV)0.7650155347
Kurtosis0.6926140641
Mean1.777787354
Median Absolute Deviation (MAD)0
Skewness1.503909528
Sum61883
Variance1.849695047
MonotocityNot monotonic
2020-11-30T23:57:29.356723image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
12437956.7%
 
534798.1%
 
228476.6%
 
421034.9%
 
320014.7%
 
(Missing)815319.0%
 
ValueCountFrequency (%) 
12437956.7%
 
228476.6%
 
320014.7%
 
421034.9%
 
534798.1%
 
ValueCountFrequency (%) 
534798.1%
 
421034.9%
 
320014.7%
 
228476.6%
 
12437956.7%
 

PLZ8_GBZ
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing8153
Missing (%)19.0%
Infinite0
Infinite (%)0.0%
Mean3.421385274
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:29.456089image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.094782984
Coefficient of variation (CV)0.3199823744
Kurtosis-0.5572427449
Mean3.421385274
Median Absolute Deviation (MAD)1
Skewness-0.1985515689
Sum119095
Variance1.198549782
MonotocityNot monotonic
2020-11-30T23:57:29.556328image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31303330.3%
 
4860020.0%
 
5698816.3%
 
2446810.4%
 
117204.0%
 
(Missing)815319.0%
 
ValueCountFrequency (%) 
117204.0%
 
2446810.4%
 
31303330.3%
 
4860020.0%
 
5698816.3%
 
ValueCountFrequency (%) 
5698816.3%
 
4860020.0%
 
31303330.3%
 
2446810.4%
 
117204.0%
 

PLZ8_HHZ
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing8153
Missing (%)19.0%
Infinite0
Infinite (%)0.0%
Mean3.537016289
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:29.664881image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9626224564
Coefficient of variation (CV)0.2721566365
Kurtosis-0.5496661491
Mean3.537016289
Median Absolute Deviation (MAD)1
Skewness-0.00204438035
Sum123120
Variance0.9266419936
MonotocityNot monotonic
2020-11-30T23:57:29.771144image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31489334.7%
 
4914221.3%
 
5694616.2%
 
233157.7%
 
15131.2%
 
(Missing)815319.0%
 
ValueCountFrequency (%) 
15131.2%
 
233157.7%
 
31489334.7%
 
4914221.3%
 
5694616.2%
 
ValueCountFrequency (%) 
5694616.2%
 
4914221.3%
 
31489334.7%
 
233157.7%
 
15131.2%
 

PRAEGENDE_JUGENDJAHRE
Real number (ℝ≥0)

ZEROS

Distinct16
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.427750105
Minimum0
Maximum15
Zeros7454
Zeros (%)17.4%
Memory size335.8 KiB
2020-11-30T23:57:29.884245image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median4
Q36
95-th percentile12
Maximum15
Range15
Interquartile range (IQR)5

Descriptive statistics

Standard deviation3.753186573
Coefficient of variation (CV)0.8476509477
Kurtosis0.206027239
Mean4.427750105
Median Absolute Deviation (MAD)3
Skewness0.8627510551
Sum190225
Variance14.08640945
MonotocityNot monotonic
2020-11-30T23:57:30.024590image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%) 
0745417.4%
 
3700216.3%
 
5582813.6%
 
1431510.0%
 
839269.1%
 
435678.3%
 
621855.1%
 
220814.8%
 
918764.4%
 
1411002.6%
 
1110992.6%
 
1010012.3%
 
156501.5%
 
74030.9%
 
123130.7%
 
131620.4%
 
ValueCountFrequency (%) 
0745417.4%
 
1431510.0%
 
220814.8%
 
3700216.3%
 
435678.3%
 
5582813.6%
 
621855.1%
 
74030.9%
 
839269.1%
 
918764.4%
 
ValueCountFrequency (%) 
156501.5%
 
1411002.6%
 
131620.4%
 
123130.7%
 
1110992.6%
 
1010012.3%
 
918764.4%
 
839269.1%
 
74030.9%
 
621855.1%
 

REGIOTYP
Real number (ℝ≥0)

MISSING
ZEROS

Distinct8
Distinct (%)< 0.1%
Missing8445
Missing (%)19.7%
Infinite0
Infinite (%)0.0%
Mean4.126227656
Minimum0
Maximum7
Zeros1485
Zeros (%)3.5%
Memory size335.8 KiB
2020-11-30T23:57:30.151618image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median5
Q36
95-th percentile7
Maximum7
Range7
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.014987779
Coefficient of variation (CV)0.4883365501
Kurtosis-1.014061662
Mean4.126227656
Median Absolute Deviation (MAD)1
Skewness-0.3807023729
Sum142425
Variance4.060175748
MonotocityNot monotonic
2020-11-30T23:57:30.247213image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
6806518.8%
 
5665115.5%
 
2470911.0%
 
3434710.1%
 
732607.6%
 
431677.4%
 
128336.6%
 
014853.5%
 
(Missing)844519.7%
 
ValueCountFrequency (%) 
014853.5%
 
128336.6%
 
2470911.0%
 
3434710.1%
 
431677.4%
 
5665115.5%
 
6806518.8%
 
732607.6%
 
ValueCountFrequency (%) 
732607.6%
 
6806518.8%
 
5665115.5%
 
431677.4%
 
3434710.1%
 
2470911.0%
 
128336.6%
 
014853.5%
 

RELAT_AB
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing7951
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean2.958098883
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:30.352788image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum9
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.3472446
Coefficient of variation (CV)0.4554427194
Kurtosis-0.9665782959
Mean2.958098883
Median Absolute Deviation (MAD)1
Skewness0.05587733084
Sum103566
Variance1.815068011
MonotocityNot monotonic
2020-11-30T23:57:30.449838image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31214028.3%
 
1701616.3%
 
5648115.1%
 
2490311.4%
 
4446410.4%
 
97< 0.1%
 
(Missing)795118.5%
 
ValueCountFrequency (%) 
1701616.3%
 
2490311.4%
 
31214028.3%
 
4446410.4%
 
5648115.1%
 
97< 0.1%
 
ValueCountFrequency (%) 
97< 0.1%
 
5648115.1%
 
4446410.4%
 
31214028.3%
 
2490311.4%
 
1701616.3%
 

RETOURTYP_BK_S
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing605
Missing (%)1.4%
Infinite0
Infinite (%)0.0%
Mean3.728592677
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:30.558777image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median3
Q35
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.179453726
Coefficient of variation (CV)0.3163267829
Kurtosis-1.167726991
Mean3.728592677
Median Absolute Deviation (MAD)1
Skewness-0.2495191133
Sum157932
Variance1.391111092
MonotocityNot monotonic
2020-11-30T23:57:30.658374image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
51715839.9%
 
31541235.9%
 
2512711.9%
 
436648.5%
 
19962.3%
 
(Missing)6051.4%
 
ValueCountFrequency (%) 
19962.3%
 
2512711.9%
 
31541235.9%
 
436648.5%
 
51715839.9%
 
ValueCountFrequency (%) 
51715839.9%
 
436648.5%
 
31541235.9%
 
2512711.9%
 
19962.3%
 

RT_KEIN_ANREIZ
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing605
Missing (%)1.4%
Infinite0
Infinite (%)0.0%
Mean2.484807706
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:30.769950image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q34
95-th percentile4
Maximum5
Range4
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.232905337
Coefficient of variation (CV)0.4961773639
Kurtosis-1.273844363
Mean2.484807706
Median Absolute Deviation (MAD)1
Skewness0.2167392224
Sum105249
Variance1.520055571
MonotocityNot monotonic
2020-11-30T23:57:30.875768image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
11233028.7%
 
41072025.0%
 
21045024.3%
 
3757317.6%
 
512843.0%
 
(Missing)6051.4%
 
ValueCountFrequency (%) 
11233028.7%
 
21045024.3%
 
3757317.6%
 
41072025.0%
 
512843.0%
 
ValueCountFrequency (%) 
512843.0%
 
41072025.0%
 
3757317.6%
 
21045024.3%
 
11233028.7%
 

RT_SCHNAEPPCHEN
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing605
Missing (%)1.4%
Infinite0
Infinite (%)0.0%
Mean4.143046014
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:30.992099image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median5
Q35
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.201549785
Coefficient of variation (CV)0.2900160368
Kurtosis0.2258746174
Mean4.143046014
Median Absolute Deviation (MAD)0
Skewness-1.203442465
Sum175487
Variance1.443721886
MonotocityNot monotonic
2020-11-30T23:57:31.092912image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
52449757.0%
 
4715216.6%
 
3478911.1%
 
241089.6%
 
118114.2%
 
(Missing)6051.4%
 
ValueCountFrequency (%) 
118114.2%
 
241089.6%
 
3478911.1%
 
4715216.6%
 
52449757.0%
 
ValueCountFrequency (%) 
52449757.0%
 
4715216.6%
 
3478911.1%
 
241089.6%
 
118114.2%
 

RT_UEBERGROESSE
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing6380
Missing (%)14.9%
Infinite0
Infinite (%)0.0%
Mean2.201902575
Minimum0
Maximum5
Zeros287
Zeros (%)0.7%
Memory size335.8 KiB
2020-11-30T23:57:31.196866image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median2
Q33
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.306469589
Coefficient of variation (CV)0.5933366914
Kurtosis-0.4136518855
Mean2.201902575
Median Absolute Deviation (MAD)1
Skewness0.8096038959
Sum80550
Variance1.706862786
MonotocityNot monotonic
2020-11-30T23:57:31.299111image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
11432533.3%
 
2944122.0%
 
3610314.2%
 
533307.8%
 
430967.2%
 
02870.7%
 
(Missing)638014.9%
 
ValueCountFrequency (%) 
02870.7%
 
11432533.3%
 
2944122.0%
 
3610314.2%
 
430967.2%
 
533307.8%
 
ValueCountFrequency (%) 
533307.8%
 
430967.2%
 
3610314.2%
 
2944122.0%
 
11432533.3%
 
02870.7%
 

SEMIO_DOM
Real number (ℝ≥0)

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.732973325
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:31.398178image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median5
Q36
95-th percentile7
Maximum7
Range6
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.556256132
Coefficient of variation (CV)0.3288115155
Kurtosis-0.5056451254
Mean4.732973325
Median Absolute Deviation (MAD)1
Skewness-0.5539731922
Sum203338
Variance2.421933148
MonotocityNot monotonic
2020-11-30T23:57:31.490495image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
61210128.2%
 
51113725.9%
 
3821519.1%
 
742159.8%
 
439689.2%
 
216994.0%
 
116273.8%
 
ValueCountFrequency (%) 
116273.8%
 
216994.0%
 
3821519.1%
 
439689.2%
 
51113725.9%
 
61210128.2%
 
742159.8%
 
ValueCountFrequency (%) 
742159.8%
 
61210128.2%
 
51113725.9%
 
439689.2%
 
3821519.1%
 
216994.0%
 
116273.8%
 

SEMIO_ERL
Real number (ℝ≥0)

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.115893115
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:31.587293image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q13
median6
Q37
95-th percentile7
Maximum7
Range6
Interquartile range (IQR)4

Descriptive statistics

Standard deviation1.824980789
Coefficient of variation (CV)0.3567277009
Kurtosis-1.632432904
Mean5.115893115
Median Absolute Deviation (MAD)1
Skewness-0.2178947079
Sum219789
Variance3.33055488
MonotocityNot monotonic
2020-11-30T23:57:31.682012image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
71721540.1%
 
31290130.0%
 
6548112.8%
 
4543712.7%
 
28311.9%
 
57971.9%
 
13000.7%
 
ValueCountFrequency (%) 
13000.7%
 
28311.9%
 
31290130.0%
 
4543712.7%
 
57971.9%
 
6548112.8%
 
71721540.1%
 
ValueCountFrequency (%) 
71721540.1%
 
6548112.8%
 
57971.9%
 
4543712.7%
 
31290130.0%
 
28311.9%
 
13000.7%
 

SEMIO_FAM
Real number (ℝ≥0)

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.762557609
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:31.782067image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median4
Q36
95-th percentile6
Maximum7
Range6
Interquartile range (IQR)4

Descriptive statistics

Standard deviation1.844612213
Coefficient of variation (CV)0.4902548758
Kurtosis-1.355286675
Mean3.762557609
Median Absolute Deviation (MAD)2
Skewness-0.010053423
Sum161647
Variance3.402594217
MonotocityNot monotonic
2020-11-30T23:57:31.873257image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
61120926.1%
 
3752617.5%
 
2730317.0%
 
1598213.9%
 
4539312.6%
 
5459410.7%
 
79552.2%
 
ValueCountFrequency (%) 
1598213.9%
 
2730317.0%
 
3752617.5%
 
4539312.6%
 
5459410.7%
 
61120926.1%
 
79552.2%
 
ValueCountFrequency (%) 
79552.2%
 
61120926.1%
 
5459410.7%
 
4539312.6%
 
3752617.5%
 
2730317.0%
 
1598213.9%
 

SEMIO_KAEM
Real number (ℝ≥0)

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.665495089
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:31.971402image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median5
Q36
95-th percentile7
Maximum7
Range6
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.723420523
Coefficient of variation (CV)0.3693971358
Kurtosis-0.8925927754
Mean4.665495089
Median Absolute Deviation (MAD)1
Skewness-0.5832553872
Sum200439
Variance2.970178299
MonotocityNot monotonic
2020-11-30T23:57:32.070311image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
61581736.8%
 
3859420.0%
 
5780418.2%
 
737198.7%
 
233697.8%
 
122245.2%
 
414353.3%
 
ValueCountFrequency (%) 
122245.2%
 
233697.8%
 
3859420.0%
 
414353.3%
 
5780418.2%
 
61581736.8%
 
737198.7%
 
ValueCountFrequency (%) 
737198.7%
 
61581736.8%
 
5780418.2%
 
414353.3%
 
3859420.0%
 
233697.8%
 
122245.2%
 

SEMIO_KRIT
Real number (ℝ≥0)

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.005982031
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:32.177087image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median6
Q37
95-th percentile7
Maximum7
Range6
Interquartile range (IQR)4

Descriptive statistics

Standard deviation1.866680663
Coefficient of variation (CV)0.3728900047
Kurtosis-0.9609347416
Mean5.005982031
Median Absolute Deviation (MAD)1
Skewness-0.4923246436
Sum215067
Variance3.484496697
MonotocityNot monotonic
2020-11-30T23:57:32.271036image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
71370231.9%
 
3949922.1%
 
6810718.9%
 
4502811.7%
 
537238.7%
 
125195.9%
 
23840.9%
 
ValueCountFrequency (%) 
125195.9%
 
23840.9%
 
3949922.1%
 
4502811.7%
 
537238.7%
 
6810718.9%
 
71370231.9%
 
ValueCountFrequency (%) 
71370231.9%
 
6810718.9%
 
537238.7%
 
4502811.7%
 
3949922.1%
 
23840.9%
 
125195.9%
 

SEMIO_KULT
Real number (ℝ≥0)

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.166658908
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:32.365908image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile6
Maximum7
Range6
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.664364929
Coefficient of variation (CV)0.5255902127
Kurtosis-0.7438281921
Mean3.166658908
Median Absolute Deviation (MAD)1
Skewness0.3667172945
Sum136046
Variance2.770110617
MonotocityNot monotonic
2020-11-30T23:57:32.455483image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
31114825.9%
 
1947422.1%
 
4744417.3%
 
2575513.4%
 
6428110.0%
 
539329.2%
 
79282.2%
 
ValueCountFrequency (%) 
1947422.1%
 
2575513.4%
 
31114825.9%
 
4744417.3%
 
539329.2%
 
6428110.0%
 
79282.2%
 
ValueCountFrequency (%) 
79282.2%
 
6428110.0%
 
539329.2%
 
4744417.3%
 
31114825.9%
 
2575513.4%
 
1947422.1%
 

SEMIO_LUST
Real number (ℝ≥0)

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.399213258
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:32.551782image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q15
median5
Q37
95-th percentile7
Maximum7
Range6
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.523510448
Coefficient of variation (CV)0.282172675
Kurtosis0.7406617284
Mean5.399213258
Median Absolute Deviation (MAD)1
Skewness-0.9292804903
Sum231961
Variance2.321084086
MonotocityNot monotonic
2020-11-30T23:57:32.646208image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
51491334.7%
 
71459734.0%
 
4524312.2%
 
6460110.7%
 
114873.5%
 
212112.8%
 
39102.1%
 
ValueCountFrequency (%) 
114873.5%
 
212112.8%
 
39102.1%
 
4524312.2%
 
51491334.7%
 
6460110.7%
 
71459734.0%
 
ValueCountFrequency (%) 
71459734.0%
 
6460110.7%
 
51491334.7%
 
4524312.2%
 
39102.1%
 
212112.8%
 
114873.5%
 

SEMIO_MAT
Real number (ℝ≥0)

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.417182627
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:32.745275image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q35
95-th percentile6
Maximum7
Range6
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.806957964
Coefficient of variation (CV)0.5287858922
Kurtosis-1.276356166
Mean3.417182627
Median Absolute Deviation (MAD)2
Skewness0.07761872488
Sum146809
Variance3.265097083
MonotocityNot monotonic
2020-11-30T23:57:32.834748image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
5959222.3%
 
1914521.3%
 
2727316.9%
 
4582913.6%
 
3532212.4%
 
6473111.0%
 
710702.5%
 
ValueCountFrequency (%) 
1914521.3%
 
2727316.9%
 
3532212.4%
 
4582913.6%
 
5959222.3%
 
6473111.0%
 
710702.5%
 
ValueCountFrequency (%) 
710702.5%
 
6473111.0%
 
5959222.3%
 
4582913.6%
 
3532212.4%
 
2727316.9%
 
1914521.3%
 

SEMIO_PFLICHT
Real number (ℝ≥0)

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.345724128
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:32.930872image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q35
95-th percentile6
Maximum7
Range6
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.570618056
Coefficient of variation (CV)0.4694403948
Kurtosis-0.8087919765
Mean3.345724128
Median Absolute Deviation (MAD)1
Skewness0.1547572243
Sum143739
Variance2.466841077
MonotocityNot monotonic
2020-11-30T23:57:33.022292image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
5967122.5%
 
2915521.3%
 
4891220.7%
 
3676615.7%
 
1618614.4%
 
713103.0%
 
69622.2%
 
ValueCountFrequency (%) 
1618614.4%
 
2915521.3%
 
3676615.7%
 
4891220.7%
 
5967122.5%
 
69622.2%
 
713103.0%
 
ValueCountFrequency (%) 
713103.0%
 
69622.2%
 
5967122.5%
 
4891220.7%
 
3676615.7%
 
2915521.3%
 
1618614.4%
 

SEMIO_RAT
Real number (ℝ≥0)

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.196266468
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:33.116882image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum7
Range6
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.278979216
Coefficient of variation (CV)0.4001478689
Kurtosis0.6106085905
Mean3.196266468
Median Absolute Deviation (MAD)1
Skewness0.4537494497
Sum137318
Variance1.635787834
MonotocityNot monotonic
2020-11-30T23:57:33.206607image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
41356331.6%
 
31267129.5%
 
2853919.9%
 
139919.3%
 
522555.2%
 
710512.4%
 
68922.1%
 
ValueCountFrequency (%) 
139919.3%
 
2853919.9%
 
31267129.5%
 
41356331.6%
 
522555.2%
 
68922.1%
 
710512.4%
 
ValueCountFrequency (%) 
710512.4%
 
68922.1%
 
522555.2%
 
41356331.6%
 
31267129.5%
 
2853919.9%
 
139919.3%
 

SEMIO_REL
Real number (ℝ≥0)

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.471789023
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:33.303792image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q35
95-th percentile7
Maximum7
Range6
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.096218519
Coefficient of variation (CV)0.6037862628
Kurtosis-0.9603598458
Mean3.471789023
Median Absolute Deviation (MAD)1
Skewness0.5465523515
Sum149155
Variance4.39413208
MonotocityNot monotonic
2020-11-30T23:57:33.383507image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
1921721.5%
 
3836619.5%
 
7822719.1%
 
2762617.8%
 
4613214.3%
 
528936.7%
 
65011.2%
 
ValueCountFrequency (%) 
1921721.5%
 
2762617.8%
 
3836619.5%
 
4613214.3%
 
528936.7%
 
65011.2%
 
7822719.1%
 
ValueCountFrequency (%) 
7822719.1%
 
65011.2%
 
528936.7%
 
4613214.3%
 
3836619.5%
 
2762617.8%
 
1921721.5%
 

SEMIO_SOZ
Real number (ℝ≥0)

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.624854523
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:33.488139image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q35
95-th percentile6
Maximum7
Range6
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.67794576
Coefficient of variation (CV)0.462900166
Kurtosis-1.222652853
Mean3.624854523
Median Absolute Deviation (MAD)1
Skewness0.2320793429
Sum155731
Variance2.815501975
MonotocityNot monotonic
2020-11-30T23:57:33.584333image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
21286129.9%
 
6761917.7%
 
4682315.9%
 
3607414.1%
 
5590713.7%
 
127506.4%
 
79282.2%
 
ValueCountFrequency (%) 
127506.4%
 
21286129.9%
 
3607414.1%
 
4682315.9%
 
5590713.7%
 
6761917.7%
 
79282.2%
 
ValueCountFrequency (%) 
79282.2%
 
6761917.7%
 
5590713.7%
 
4682315.9%
 
3607414.1%
 
21286129.9%
 
127506.4%
 

SEMIO_TRADV
Real number (ℝ≥0)

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.785554676
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:33.675988image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum7
Range6
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.338822988
Coefficient of variation (CV)0.4806306618
Kurtosis0.609000932
Mean2.785554676
Median Absolute Deviation (MAD)1
Skewness0.5536524565
Sum119673
Variance1.792446992
MonotocityNot monotonic
2020-11-30T23:57:33.756203image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
31641138.2%
 
11000923.3%
 
4837319.5%
 
2548612.8%
 
69582.2%
 
59282.2%
 
77971.9%
 
ValueCountFrequency (%) 
11000923.3%
 
2548612.8%
 
31641138.2%
 
4837319.5%
 
59282.2%
 
69582.2%
 
77971.9%
 
ValueCountFrequency (%) 
77971.9%
 
69582.2%
 
59282.2%
 
4837319.5%
 
31641138.2%
 
2548612.8%
 
11000923.3%
 

SEMIO_VERT
Real number (ℝ≥0)

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.886620735
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:33.842103image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median4
Q36
95-th percentile7
Maximum7
Range6
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.103138486
Coefficient of variation (CV)0.5411226434
Kurtosis-1.337630141
Mean3.886620735
Median Absolute Deviation (MAD)2
Skewness0.01014991775
Sum166977
Variance4.42319149
MonotocityNot monotonic
2020-11-30T23:57:33.926174image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
1866120.2%
 
4672415.7%
 
7639214.9%
 
5612714.3%
 
2576213.4%
 
6554312.9%
 
337538.7%
 
ValueCountFrequency (%) 
1866120.2%
 
2576213.4%
 
337538.7%
 
4672415.7%
 
5612714.3%
 
6554312.9%
 
7639214.9%
 
ValueCountFrequency (%) 
7639214.9%
 
6554312.9%
 
5612714.3%
 
4672415.7%
 
337538.7%
 
2576213.4%
 
1866120.2%
 

SHOPPER_TYP
Real number (ℝ)

ZEROS

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.307364648
Minimum-1
Maximum3
Zeros6034
Zeros (%)14.0%
Memory size335.8 KiB
2020-11-30T23:57:34.027298image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum-1
5-th percentile-1
Q10
median1
Q33
95-th percentile3
Maximum3
Range4
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.472972521
Coefficient of variation (CV)1.126673055
Kurtosis-1.307955867
Mean1.307364648
Median Absolute Deviation (MAD)1
Skewness-0.2588039121
Sum56167
Variance2.169648049
MonotocityNot monotonic
2020-11-30T23:57:34.138381image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31380732.1%
 
1930521.7%
 
-1739717.2%
 
2641914.9%
 
0603414.0%
 
ValueCountFrequency (%) 
-1739717.2%
 
0603414.0%
 
1930521.7%
 
2641914.9%
 
31380732.1%
 
ValueCountFrequency (%) 
31380732.1%
 
2641914.9%
 
1930521.7%
 
0603414.0%
 
-1739717.2%
 

SOHO_KZ
Boolean

MISSING

Distinct2
Distinct (%)< 0.1%
Missing6969
Missing (%)16.2%
Memory size335.8 KiB
0
35645 
1
 
348
(Missing)
6969 
ValueCountFrequency (%) 
03564583.0%
 
13480.8%
 
(Missing)696916.2%
 

STRUKTURTYP
Categorical

MISSING

Distinct3
Distinct (%)< 0.1%
Missing7955
Missing (%)18.5%
Memory size335.8 KiB
3
23303 
1
6569 
2
5135 
ValueCountFrequency (%) 
32330354.2%
 
1656915.3%
 
2513512.0%
 
(Missing)795518.5%
 
2020-11-30T23:57:34.288941image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters7
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
.3500727.2%
 
03500727.2%
 
32330318.1%
 
n1591012.3%
 
a79556.2%
 
165695.1%
 
251354.0%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number7001454.3%
 
Other Punctuation3500727.2%
 
Lowercase Letter2386518.5%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
03500750.0%
 
32330333.3%
 
165699.4%
 
251357.3%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
.35007100.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n1591066.7%
 
a795533.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Common10502181.5%
 
Latin2386518.5%
 

Most frequent Common characters

ValueCountFrequency (%) 
.3500733.3%
 
03500733.3%
 
32330322.2%
 
165696.3%
 
251354.9%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n1591066.7%
 
a795533.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII128886100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
.3500727.2%
 
03500727.2%
 
32330318.1%
 
n1591012.3%
 
a79556.2%
 
165695.1%
 
251354.0%
 

TITEL_KZ
Real number (ℝ≥0)

MISSING
SKEWED
ZEROS

Distinct5
Distinct (%)< 0.1%
Missing6969
Missing (%)16.2%
Infinite0
Infinite (%)0.0%
Mean0.007918206318
Minimum0
Maximum5
Zeros35780
Zeros (%)83.3%
Memory size335.8 KiB
2020-11-30T23:57:34.392372image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum5
Range5
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.1283306343
Coefficient of variation (CV)16.20703341
Kurtosis826.1893767
Mean0.007918206318
Median Absolute Deviation (MAD)0
Skewness25.64853276
Sum285
Variance0.0164687517
MonotocityNot monotonic
2020-11-30T23:57:34.490457image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
03578083.3%
 
11900.4%
 
410< 0.1%
 
58< 0.1%
 
35< 0.1%
 
(Missing)696916.2%
 
ValueCountFrequency (%) 
03578083.3%
 
11900.4%
 
35< 0.1%
 
410< 0.1%
 
58< 0.1%
 
ValueCountFrequency (%) 
58< 0.1%
 
410< 0.1%
 
35< 0.1%
 
11900.4%
 
03578083.3%
 

UMFELD_ALT
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7925
Missing (%)18.4%
Infinite0
Infinite (%)0.0%
Mean2.86482861
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:34.587565image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.295502203
Coefficient of variation (CV)0.452209322
Kurtosis-1.079509414
Mean2.86482861
Median Absolute Deviation (MAD)1
Skewness0.03767065536
Sum100375
Variance1.678325959
MonotocityNot monotonic
2020-11-30T23:57:34.683266image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
3934221.7%
 
4757617.6%
 
1698516.3%
 
2687016.0%
 
542649.9%
 
(Missing)792518.4%
 
ValueCountFrequency (%) 
1698516.3%
 
2687016.0%
 
3934221.7%
 
4757617.6%
 
542649.9%
 
ValueCountFrequency (%) 
542649.9%
 
4757617.6%
 
3934221.7%
 
2687016.0%
 
1698516.3%
 

UMFELD_JUNG
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7925
Missing (%)18.4%
Infinite0
Infinite (%)0.0%
Mean4.268573223
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:34.787358image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q14
median5
Q35
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9930217471
Coefficient of variation (CV)0.232635519
Kurtosis1.485520329
Mean4.268573223
Median Absolute Deviation (MAD)0
Skewness-1.412341897
Sum149558
Variance0.9860921902
MonotocityNot monotonic
2020-11-30T23:57:34.887857image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
51919044.7%
 
4928221.6%
 
341889.7%
 
215393.6%
 
18382.0%
 
(Missing)792518.4%
 
ValueCountFrequency (%) 
18382.0%
 
215393.6%
 
341889.7%
 
4928221.6%
 
51919044.7%
 
ValueCountFrequency (%) 
51919044.7%
 
4928221.6%
 
341889.7%
 
215393.6%
 
18382.0%
 

UNGLEICHENN_FLAG
Boolean

MISSING

Distinct2
Distinct (%)< 0.1%
Missing6969
Missing (%)16.2%
Memory size335.8 KiB
0
33428 
1
 
2565
(Missing)
6969 
ValueCountFrequency (%) 
03342877.8%
 
125656.0%
 
(Missing)696916.2%
 

VERDICHTUNGSRAUM
Real number (ℝ≥0)

MISSING
ZEROS

Distinct46
Distinct (%)0.1%
Missing7955
Missing (%)18.5%
Infinite0
Infinite (%)0.0%
Mean4.465992516
Minimum0
Maximum45
Zeros17087
Zeros (%)39.8%
Memory size335.8 KiB
2020-11-30T23:57:35.036127image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q34
95-th percentile25
Maximum45
Range45
Interquartile range (IQR)4

Descriptive statistics

Standard deviation8.460627756
Coefficient of variation (CV)1.894456322
Kurtosis6.943314325
Mean4.465992516
Median Absolute Deviation (MAD)1
Skewness2.634332856
Sum156341
Variance71.58222202
MonotocityNot monotonic
2020-11-30T23:57:35.168952image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%) 
01708739.8%
 
138048.9%
 
224035.6%
 
316563.9%
 
413643.2%
 
68922.1%
 
58702.0%
 
95071.2%
 
85041.2%
 
74931.1%
 
124341.0%
 
104261.0%
 
144201.0%
 
133550.8%
 
112940.7%
 
152800.7%
 
172430.6%
 
182310.5%
 
162210.5%
 
241670.4%
 
271660.4%
 
191580.4%
 
201320.3%
 
251300.3%
 
321240.3%
 
Other values (21)16463.8%
 
(Missing)795518.5%
 
ValueCountFrequency (%) 
01708739.8%
 
138048.9%
 
224035.6%
 
316563.9%
 
413643.2%
 
58702.0%
 
68922.1%
 
74931.1%
 
85041.2%
 
95071.2%
 
ValueCountFrequency (%) 
45700.2%
 
44810.2%
 
43950.2%
 
42460.1%
 
41260.1%
 
40520.1%
 
39550.1%
 
38820.2%
 
37710.2%
 
361040.2%
 

VERS_TYP
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size335.8 KiB
1
18540 
2
17025 
-1
7397 
ValueCountFrequency (%) 
11854043.2%
 
21702539.6%
 
-1739717.2%
 
2020-11-30T23:57:35.289498image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters3
Unique unicode categories2 ?
Unique unicode scripts1 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
12593751.5%
 
21702533.8%
 
-739714.7%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number4296285.3%
 
Dash Punctuation739714.7%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
12593760.4%
 
21702539.6%
 

Most frequent Dash Punctuation characters

ValueCountFrequency (%) 
-7397100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Common50359100.0%
 

Most frequent Common characters

ValueCountFrequency (%) 
12593751.5%
 
21702533.8%
 
-739714.7%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII50359100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
12593751.5%
 
21702533.8%
 
-739714.7%
 

VHA
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing6969
Missing (%)16.2%
Infinite0
Infinite (%)0.0%
Mean1.137443392
Minimum0
Maximum5
Zeros16176
Zeros (%)37.7%
Memory size335.8 KiB
2020-11-30T23:57:35.389990image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q31
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.553994733
Coefficient of variation (CV)1.366217207
Kurtosis0.9954126717
Mean1.137443392
Median Absolute Deviation (MAD)1
Skewness1.502467609
Sum40940
Variance2.414899632
MonotocityNot monotonic
2020-11-30T23:57:35.497641image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
01617637.7%
 
11302730.3%
 
530207.0%
 
317614.1%
 
417564.1%
 
22530.6%
 
(Missing)696916.2%
 
ValueCountFrequency (%) 
01617637.7%
 
11302730.3%
 
22530.6%
 
317614.1%
 
417564.1%
 
530207.0%
 
ValueCountFrequency (%) 
530207.0%
 
417564.1%
 
317614.1%
 
22530.6%
 
11302730.3%
 
01617637.7%
 

VHN
Real number (ℝ≥0)

MISSING
ZEROS

Distinct5
Distinct (%)< 0.1%
Missing8445
Missing (%)19.7%
Infinite0
Infinite (%)0.0%
Mean2.384737955
Minimum0
Maximum4
Zeros1485
Zeros (%)3.5%
Memory size335.8 KiB
2020-11-30T23:57:35.589133image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median2
Q33
95-th percentile4
Maximum4
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.14825115
Coefficient of variation (CV)0.4814999264
Kurtosis-0.9121218272
Mean2.384737955
Median Absolute Deviation (MAD)1
Skewness-0.09286658389
Sum82314
Variance1.318480703
MonotocityNot monotonic
2020-11-30T23:57:35.675805image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
21098925.6%
 
3782918.2%
 
4754517.6%
 
1666915.5%
 
014853.5%
 
(Missing)844519.7%
 
ValueCountFrequency (%) 
014853.5%
 
1666915.5%
 
21098925.6%
 
3782918.2%
 
4754517.6%
 
ValueCountFrequency (%) 
4754517.6%
 
3782918.2%
 
21098925.6%
 
1666915.5%
 
014853.5%
 

VK_DHT4A
Real number (ℝ≥0)

MISSING

Distinct11
Distinct (%)< 0.1%
Missing7267
Missing (%)16.9%
Infinite0
Infinite (%)0.0%
Mean4.318644068
Minimum1
Maximum11
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:35.782367image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median3
Q37
95-th percentile10
Maximum11
Range10
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.165198775
Coefficient of variation (CV)0.732914944
Kurtosis-1.243628625
Mean4.318644068
Median Absolute Deviation (MAD)2
Skewness0.4549453147
Sum154154
Variance10.01848328
MonotocityNot monotonic
2020-11-30T23:57:35.868565image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%) 
11090025.4%
 
2438710.2%
 
730177.0%
 
1029416.8%
 
627956.5%
 
326196.1%
 
924415.7%
 
422715.3%
 
822015.1%
 
521154.9%
 
118< 0.1%
 
(Missing)726716.9%
 
ValueCountFrequency (%) 
11090025.4%
 
2438710.2%
 
326196.1%
 
422715.3%
 
521154.9%
 
627956.5%
 
730177.0%
 
822015.1%
 
924415.7%
 
1029416.8%
 
ValueCountFrequency (%) 
118< 0.1%
 
1029416.8%
 
924415.7%
 
822015.1%
 
730177.0%
 
627956.5%
 
521154.9%
 
422715.3%
 
326196.1%
 
2438710.2%
 

VK_DISTANZ
Real number (ℝ≥0)

MISSING

Distinct13
Distinct (%)< 0.1%
Missing7267
Missing (%)16.9%
Infinite0
Infinite (%)0.0%
Mean4.505953215
Minimum1
Maximum13
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:35.951058image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median4
Q37
95-th percentile11
Maximum13
Range12
Interquartile range (IQR)5

Descriptive statistics

Standard deviation3.289502061
Coefficient of variation (CV)0.7300346683
Kurtosis-0.5301004379
Mean4.505953215
Median Absolute Deviation (MAD)3
Skewness0.7047166047
Sum160840
Variance10.82082381
MonotocityNot monotonic
2020-11-30T23:57:36.043270image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%) 
1865220.1%
 
2536212.5%
 
641609.7%
 
334828.1%
 
430057.0%
 
729696.9%
 
819664.6%
 
915173.5%
 
511982.8%
 
1010492.4%
 
1110382.4%
 
128852.1%
 
134121.0%
 
(Missing)726716.9%
 
ValueCountFrequency (%) 
1865220.1%
 
2536212.5%
 
334828.1%
 
430057.0%
 
511982.8%
 
641609.7%
 
729696.9%
 
819664.6%
 
915173.5%
 
1010492.4%
 
ValueCountFrequency (%) 
134121.0%
 
128852.1%
 
1110382.4%
 
1010492.4%
 
915173.5%
 
819664.6%
 
729696.9%
 
641609.7%
 
511982.8%
 
430057.0%
 

VK_ZG11
Real number (ℝ≥0)

MISSING

Distinct11
Distinct (%)< 0.1%
Missing7267
Missing (%)16.9%
Infinite0
Infinite (%)0.0%
Mean3.11696316
Minimum1
Maximum11
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:36.145006image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q34
95-th percentile9
Maximum11
Range10
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.534331308
Coefficient of variation (CV)0.813077081
Kurtosis1.015065081
Mean3.11696316
Median Absolute Deviation (MAD)1
Skewness1.33750966
Sum111260
Variance6.422835177
MonotocityNot monotonic
2020-11-30T23:57:36.260833image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%) 
11334431.1%
 
2570313.3%
 
3518012.1%
 
435548.3%
 
521905.1%
 
615113.5%
 
99702.3%
 
79602.2%
 
109572.2%
 
89562.2%
 
113700.9%
 
(Missing)726716.9%
 
ValueCountFrequency (%) 
11334431.1%
 
2570313.3%
 
3518012.1%
 
435548.3%
 
521905.1%
 
615113.5%
 
79602.2%
 
89562.2%
 
99702.3%
 
109572.2%
 
ValueCountFrequency (%) 
113700.9%
 
109572.2%
 
99702.3%
 
89562.2%
 
79602.2%
 
615113.5%
 
521905.1%
 
435548.3%
 
3518012.1%
 
2570313.3%
 

W_KEIT_KIND_HH
Real number (ℝ≥0)

MISSING
ZEROS

Distinct7
Distinct (%)< 0.1%
Missing9678
Missing (%)22.5%
Infinite0
Infinite (%)0.0%
Mean4.488402836
Minimum0
Maximum6
Zeros739
Zeros (%)1.7%
Memory size335.8 KiB
2020-11-30T23:57:36.354240image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q13
median6
Q36
95-th percentile6
Maximum6
Range6
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.889573269
Coefficient of variation (CV)0.4209901246
Kurtosis-0.8619692857
Mean4.488402836
Median Absolute Deviation (MAD)0
Skewness-0.7885563894
Sum149392
Variance3.57048714
MonotocityNot monotonic
2020-11-30T23:57:36.439276image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
61815242.3%
 
2473911.0%
 
434188.0%
 
326376.1%
 
121445.0%
 
514553.4%
 
07391.7%
 
(Missing)967822.5%
 
ValueCountFrequency (%) 
07391.7%
 
121445.0%
 
2473911.0%
 
326376.1%
 
434188.0%
 
514553.4%
 
61815242.3%
 
ValueCountFrequency (%) 
61815242.3%
 
514553.4%
 
434188.0%
 
326376.1%
 
2473911.0%
 
121445.0%
 
07391.7%
 

WOHNDAUER_2008
Real number (ℝ≥0)

MISSING

Distinct9
Distinct (%)< 0.1%
Missing6969
Missing (%)16.2%
Infinite0
Infinite (%)0.0%
Mean8.72994749
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:36.532707image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile7
Q19
median9
Q39
95-th percentile9
Maximum9
Range8
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.010545222
Coefficient of variation (CV)0.1157561627
Kurtosis19.35655156
Mean8.72994749
Median Absolute Deviation (MAD)0
Skewness-4.360986433
Sum314217
Variance1.021201645
MonotocityNot monotonic
2020-11-30T23:57:36.640216image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%) 
93247875.6%
 
815093.5%
 
44611.1%
 
64191.0%
 
53820.9%
 
73540.8%
 
33460.8%
 
1290.1%
 
215< 0.1%
 
(Missing)696916.2%
 
ValueCountFrequency (%) 
1290.1%
 
215< 0.1%
 
33460.8%
 
44611.1%
 
53820.9%
 
64191.0%
 
73540.8%
 
815093.5%
 
93247875.6%
 
ValueCountFrequency (%) 
93247875.6%
 
815093.5%
 
73540.8%
 
64191.0%
 
53820.9%
 
44611.1%
 
33460.8%
 
215< 0.1%
 
1290.1%
 

WOHNLAGE
Real number (ℝ≥0)

MISSING

Distinct8
Distinct (%)< 0.1%
Missing7777
Missing (%)18.1%
Infinite0
Infinite (%)0.0%
Mean4.059684525
Minimum0
Maximum8
Zeros127
Zeros (%)0.3%
Memory size335.8 KiB
2020-11-30T23:57:36.753346image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q13
median3
Q37
95-th percentile7
Maximum8
Range8
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.046696937
Coefficient of variation (CV)0.5041517203
Kurtosis-1.129424703
Mean4.059684525
Median Absolute Deviation (MAD)1
Skewness0.4193841576
Sum142840
Variance4.188968352
MonotocityNot monotonic
2020-11-30T23:57:36.855946image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
31134226.4%
 
7912421.2%
 
2500111.6%
 
4455910.6%
 
124735.8%
 
520794.8%
 
84801.1%
 
01270.3%
 
(Missing)777718.1%
 
ValueCountFrequency (%) 
01270.3%
 
124735.8%
 
2500111.6%
 
31134226.4%
 
4455910.6%
 
520794.8%
 
7912421.2%
 
84801.1%
 
ValueCountFrequency (%) 
84801.1%
 
7912421.2%
 
520794.8%
 
4455910.6%
 
31134226.4%
 
2500111.6%
 
124735.8%
 
01270.3%
 

ZABEOTYP
Real number (ℝ≥0)

Distinct6
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.80419906
Minimum1
Maximum6
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:36.970859image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median3
Q33
95-th percentile4
Maximum6
Range5
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.121585077
Coefficient of variation (CV)0.3999662839
Kurtosis1.15885187
Mean2.80419906
Median Absolute Deviation (MAD)0
Skewness0.2647619627
Sum120474
Variance1.257953085
MonotocityNot monotonic
2020-11-30T23:57:37.073219image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
32695862.7%
 
1838519.5%
 
441339.6%
 
617054.0%
 
214843.5%
 
52970.7%
 
ValueCountFrequency (%) 
1838519.5%
 
214843.5%
 
32695862.7%
 
441339.6%
 
52970.7%
 
617054.0%
 
ValueCountFrequency (%) 
617054.0%
 
52970.7%
 
441339.6%
 
32695862.7%
 
214843.5%
 
1838519.5%
 

RESPONSE
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size335.8 KiB
0
42430 
1
 
532
ValueCountFrequency (%) 
04243098.8%
 
15321.2%
 

ANREDE_KZ
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size335.8 KiB
2
25566 
1
17396 
ValueCountFrequency (%) 
22556659.5%
 
11739640.5%
 
2020-11-30T23:57:37.192394image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters2
Unique unicode categories1 ?
Unique unicode scripts1 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
22556659.5%
 
11739640.5%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number42962100.0%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
22556659.5%
 
11739640.5%
 

Most occurring scripts

ValueCountFrequency (%) 
Common42962100.0%
 

Most frequent Common characters

ValueCountFrequency (%) 
22556659.5%
 
11739640.5%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII42962100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
22556659.5%
 
11739640.5%
 

ALTERSKATEGORIE_GROB
Real number (ℝ≥0)

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.213909967
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size335.8 KiB
2020-11-30T23:57:37.300313image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median4
Q34
95-th percentile4
Maximum9
Range8
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.06747483
Coefficient of variation (CV)0.3321421074
Kurtosis1.260028535
Mean3.213909967
Median Absolute Deviation (MAD)0
Skewness-0.7334021832
Sum138076
Variance1.139502512
MonotocityNot monotonic
2020-11-30T23:57:37.400565image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
42290653.3%
 
31122126.1%
 
1544812.7%
 
233067.7%
 
9810.2%
 
ValueCountFrequency (%) 
1544812.7%
 
233067.7%
 
31122126.1%
 
42290653.3%
 
9810.2%
 
ValueCountFrequency (%) 
9810.2%
 
42290653.3%
 
31122126.1%
 
233067.7%
 
1544812.7%